In modern and crowded traffic life, it becomes mandatory to save the human life by reaching the hospital very sooner than possible. This paper explains about the advancement in tracking the ambulance presence amidst the traffic with the usage of GPS tracking system calculating the position of the ambulance from the traffic signal which replaces the RF transmitter receiver circuitry. This paper also retains the use of the image capturing technology available from the base paper (IMPACT OF IMAGE PROCESSING IN SAVING THE HUMAN LIFE BY AUTOMATING TRAFFIC SIGNALS) to identify the presence of the ambulance, thereby changing the signal to green automatically in favour of ambulance.
Conventional non-vision based navigation systems relying on purely Global Positioning System (GPS) or inertial sensors can provide the 3D position or orientation of the user. However GPS is often not available in forested regions and cannot be used indoors. Visual odometry provides an independent method to estimate position and orientation of the user/system based on the images captured by the moving user accurately. Vision based systems also provide information (e.g. images, 3D location of landmarks, detection of scene objects) about the scene that the user is looking at. In this project, a set of techniques are used for the accurate pose and position estimation of the moving vehicle for autonomous navigation using the images obtained from two cameras placed at two different locations of the same area on the top of the vehicle. These cases are referred to as stereo vision. Stereo vision provides a method for the 3D reconstruction of the environment which is required for pose and position estimation. Firstly, a set of images are captured. The Harris corner detector is utilized to automatically extract a set of feature points from the images and then feature matching is done using correlation based matching. Triangulation is applied on feature points to find the 3D co-ordinates. Next, a new set of images is captured. Then repeat the same technique for the new set of images too. Finally, by using the 3D feature points, obtained from the first set of images and the new set of images, the pose and position estimation of moving vehicle is done using QUEST algorithm.
Obstacle detection for autonomous systems using stereoscopic images and bacte...IJECEIAES
This paper presents a low cost strategy for real-time estimation of the position of ob- stacles in an unknown environment for autonomous robots. The strategy was intended for use in autonomous service robots, which navigate in unknown and dynamic indoor environments. In addition to human interaction, these environments are characterized by a design created for the human being, which is why our developments seek morphological and functional similarity equivalent to the human model. We use a pair of cameras on our robot to achieve a stereoscopic vision of the environment, and we analyze this information to determine the distance to obstacles using an algorithm that mimics bacterial behavior. The algorithm was evaluated on our robotic platform demonstrating high performance in the location of obstacles and real-time operation.
Visual Mapping and Collision Avoidance Dynamic Environments in Dynamic Enviro...Darius Burschka
How conventional vision is more appropriate for control since it provides also error analysis. There is a lot of information in the images that is lost when converting to 3D
Intelligent indoor mobile robot navigation using stereo visionsipij
Majority of the existing robot navigation systems, which facilitate the use of laser range finders, sonar
sensors or artificial landmarks, has the ability to locate itself in an unknown environment and then build a
map of the corresponding environment. Stereo vision,while still being a rapidly developing technique in the
field of autonomous mobile robots, are currently less preferable due to its high implementation cost. This
paper aims at describing an experimental approach for the building of a stereo vision system that helps the
robots to avoid obstacles and navigate through indoor environments and at the same time remaining very
much cost effective. This paper discusses the fusion techniques of stereo vision and ultrasound sensors
which helps in the successful navigation through different types of complex environments. The data from
the sensor enables the robot to create the two dimensional topological map of unknown environments and
stereo vision systems models the three dimension model of the same environment.
Pedestrian Counting in Video Sequences based on Optical Flow ClusteringCSCJournals
The demand for automatic counting of pedestrians at event sites, buildings, or streets has been increased. Existing systems for counting pedestrians in video sequences have a problem that counting accuracy degrades when many pedestrians coexist and occlusion occurs frequently. In this paper, we introduce a method of clustering optical flows extracted from pedestrians in video frames to improve the counting accuracy. The proposed method counts the number of pedestrians by using pre-learned statistics, based on the strong correlation between the number of optical flow clusters and the actual number of pedestrians. We evaluate the accuracy of the proposed method using several video sequences, focusing in particular on the effect of parameters for optical flow clustering. We find that the proposed method improves the counting accuracy by up to 25% as compared with a non-clustering method. We also report that using a clustering threshold of angles less than 1 degree is effective for enhancing counting accuracy. Furthermore, we compare the performance of two algorithms that use feature points and lattice points when optical flows are detected. We confirm that the counting accuracy using feature points is higher than that using lattice points especially when the number of occluded pedestrians increases.
Robust and Efficient Coupling of Perception to Actuation with Metric and Non-...Darius Burschka
The talk motivates a re-thinking of the way, how perception passes the information to the control modules. Metric information is not a native space of the camera and apparently also not used in biology for navigation. Early abstraction of information from images loses a lot of important information that can be directly used for following (Visual-Servoing), motion estimation(Motion Blurr), and collision relations(Optical Flow Clustering). I present in this talk ways, how we use the image information in "classical way" that does not require any learning and runs on low-power CPUs.
1) Fourier analysis transforms images from the spatial domain to the frequency domain, allowing images to be manipulated in unexpected ways.
2) It represents any signal as a sum of sinusoids, encoding spatial frequency, magnitude, and phase information for each pixel.
3) This frequency domain representation can then be modified and transformed back, providing a means to filter images and extract geometric information.
Scattering optical tomography with discretized path integralToru Tamaki
Slide of the talks:
Toru Tamaki, Scattering tomography with path integral, Séminaire A3SI (Algorithmes, architectures, analyse et synthèse d’images), Laboratoire d'Informatique Gaspard-Monge (LIGM), ESIEE Paris, Université Paris-Est, 11-June-2015.
Toru Tamaki, Scattering optical tomography with discretized path integral, Fachbereich Computerwissenschaften, Universität Salzburg, Austria, 03-December-2015.
Toru Tamaki, Scattering optical tomography with discretized path integral, Departamento de Ciências da Informação e da Decisão em Saúde Faculdade de Medicina, Universidade do Porto, Porto, Portugal, 11-December-2015.
Conventional non-vision based navigation systems relying on purely Global Positioning System (GPS) or inertial sensors can provide the 3D position or orientation of the user. However GPS is often not available in forested regions and cannot be used indoors. Visual odometry provides an independent method to estimate position and orientation of the user/system based on the images captured by the moving user accurately. Vision based systems also provide information (e.g. images, 3D location of landmarks, detection of scene objects) about the scene that the user is looking at. In this project, a set of techniques are used for the accurate pose and position estimation of the moving vehicle for autonomous navigation using the images obtained from two cameras placed at two different locations of the same area on the top of the vehicle. These cases are referred to as stereo vision. Stereo vision provides a method for the 3D reconstruction of the environment which is required for pose and position estimation. Firstly, a set of images are captured. The Harris corner detector is utilized to automatically extract a set of feature points from the images and then feature matching is done using correlation based matching. Triangulation is applied on feature points to find the 3D co-ordinates. Next, a new set of images is captured. Then repeat the same technique for the new set of images too. Finally, by using the 3D feature points, obtained from the first set of images and the new set of images, the pose and position estimation of moving vehicle is done using QUEST algorithm.
Obstacle detection for autonomous systems using stereoscopic images and bacte...IJECEIAES
This paper presents a low cost strategy for real-time estimation of the position of ob- stacles in an unknown environment for autonomous robots. The strategy was intended for use in autonomous service robots, which navigate in unknown and dynamic indoor environments. In addition to human interaction, these environments are characterized by a design created for the human being, which is why our developments seek morphological and functional similarity equivalent to the human model. We use a pair of cameras on our robot to achieve a stereoscopic vision of the environment, and we analyze this information to determine the distance to obstacles using an algorithm that mimics bacterial behavior. The algorithm was evaluated on our robotic platform demonstrating high performance in the location of obstacles and real-time operation.
Visual Mapping and Collision Avoidance Dynamic Environments in Dynamic Enviro...Darius Burschka
How conventional vision is more appropriate for control since it provides also error analysis. There is a lot of information in the images that is lost when converting to 3D
Intelligent indoor mobile robot navigation using stereo visionsipij
Majority of the existing robot navigation systems, which facilitate the use of laser range finders, sonar
sensors or artificial landmarks, has the ability to locate itself in an unknown environment and then build a
map of the corresponding environment. Stereo vision,while still being a rapidly developing technique in the
field of autonomous mobile robots, are currently less preferable due to its high implementation cost. This
paper aims at describing an experimental approach for the building of a stereo vision system that helps the
robots to avoid obstacles and navigate through indoor environments and at the same time remaining very
much cost effective. This paper discusses the fusion techniques of stereo vision and ultrasound sensors
which helps in the successful navigation through different types of complex environments. The data from
the sensor enables the robot to create the two dimensional topological map of unknown environments and
stereo vision systems models the three dimension model of the same environment.
Pedestrian Counting in Video Sequences based on Optical Flow ClusteringCSCJournals
The demand for automatic counting of pedestrians at event sites, buildings, or streets has been increased. Existing systems for counting pedestrians in video sequences have a problem that counting accuracy degrades when many pedestrians coexist and occlusion occurs frequently. In this paper, we introduce a method of clustering optical flows extracted from pedestrians in video frames to improve the counting accuracy. The proposed method counts the number of pedestrians by using pre-learned statistics, based on the strong correlation between the number of optical flow clusters and the actual number of pedestrians. We evaluate the accuracy of the proposed method using several video sequences, focusing in particular on the effect of parameters for optical flow clustering. We find that the proposed method improves the counting accuracy by up to 25% as compared with a non-clustering method. We also report that using a clustering threshold of angles less than 1 degree is effective for enhancing counting accuracy. Furthermore, we compare the performance of two algorithms that use feature points and lattice points when optical flows are detected. We confirm that the counting accuracy using feature points is higher than that using lattice points especially when the number of occluded pedestrians increases.
Robust and Efficient Coupling of Perception to Actuation with Metric and Non-...Darius Burschka
The talk motivates a re-thinking of the way, how perception passes the information to the control modules. Metric information is not a native space of the camera and apparently also not used in biology for navigation. Early abstraction of information from images loses a lot of important information that can be directly used for following (Visual-Servoing), motion estimation(Motion Blurr), and collision relations(Optical Flow Clustering). I present in this talk ways, how we use the image information in "classical way" that does not require any learning and runs on low-power CPUs.
1) Fourier analysis transforms images from the spatial domain to the frequency domain, allowing images to be manipulated in unexpected ways.
2) It represents any signal as a sum of sinusoids, encoding spatial frequency, magnitude, and phase information for each pixel.
3) This frequency domain representation can then be modified and transformed back, providing a means to filter images and extract geometric information.
Scattering optical tomography with discretized path integralToru Tamaki
Slide of the talks:
Toru Tamaki, Scattering tomography with path integral, Séminaire A3SI (Algorithmes, architectures, analyse et synthèse d’images), Laboratoire d'Informatique Gaspard-Monge (LIGM), ESIEE Paris, Université Paris-Est, 11-June-2015.
Toru Tamaki, Scattering optical tomography with discretized path integral, Fachbereich Computerwissenschaften, Universität Salzburg, Austria, 03-December-2015.
Toru Tamaki, Scattering optical tomography with discretized path integral, Departamento de Ciências da Informação e da Decisão em Saúde Faculdade de Medicina, Universidade do Porto, Porto, Portugal, 11-December-2015.
The Machine Vision and Perception Group at the Technical University of Munich conducts research on visual perception and its application to medical, mobile, and human-computer interaction systems. This includes areas like registration of rigid and deformable objects, monocular reconstruction, visual localization and mapping, and biologically inspired navigation and action analysis. The group develops algorithms for tasks like 3D object recognition in point clouds that are robust to incomplete and noisy data.
This document describes a study that used the curvelets transform method to identify abnormalities in MRI images. It begins with an abstract that outlines using curvelets to analyze different MRI image formats and calculate metrics like mean squared error and peak signal-to-noise ratio to evaluate image quality. The document then provides background on curvelets, wavelets, discrete wavelet transforms, and other digital image processing concepts. It describes applying curvelets and other methods to segment MRI images and identify abnormalities. The document presents results of applying curvelets versus other methods to several MRI images and concludes that curvelets provided more accurate and significant results for frequency and time representation with higher quality than older wavelet-based methods.
Heap graph, software birthmark, frequent sub graph mining.iosrjce
IOSR Journal of Computer Engineering (IOSR-JCE) is a double blind peer reviewed International Journal that provides rapid publication (within a month) of articles in all areas of computer engineering and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications in computer technology. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
Autonomous Path Planning and Navigation of a Mobile Robot with Multi-Sensors ...CSCJournals
The mobile robot is applied widely and investigated deeply in industrial fields, meanwhile, mobile robot autonomous path planning and navigation algorithm is a hot research topic. In this paper, firstly mobile robot is introduced, the general path planning and navigation algorithms of the mobile robot are reviewed, then a fuzzy logic with filter smoothing is proposed based on the data from the laser scan sensor and GPS module, which is useful for mobile robot to find the best path to the destination automatically according to the position and size of the gaps between the obstacles in the dynamic environment, finally our designed mobile robot and corresponding Android APP are introduced, the path planning and navigation algorithms are tested on this mobile robot, the testing result shows that this algorithm is globally optimized, quickly responded, battery power and hardware cost saved compared with other algorithms, it is suitable for the mobile robot that is running on the embedded system and it can satisfy our design requirement.
The document proposes a hybrid approach for segmenting brain tumors in MRI images using wavelet and watershed transforms. It begins with applying wavelet transform to produce approximation and detail images for noise reduction. Edge detection is then performed on the approximation image. Watershed transform is applied for initial segmentation at low resolution. Repeated inverse wavelet transform is used to increase the segmented image resolution. Region merging is applied for further segmentation refinement before cropping the tumor area. The results show this coactive wavelet-watershed approach can help achieve accurate tumor segmentation.
Super resolution imaging using frequency wavelets and three dimensionalIAEME Publication
This document describes a method for achieving super resolution imaging using frequency wavelets and three-dimensional views with holographic technique. The method involves three main steps: 1) Registering low resolution images taken of the same specimen from different angles using digital holographic equipment to determine sub-pixel shifts between images; 2) Performing interpolation using frequency wavelet methods to increase resolution and add high frequency information; 3) Reconstructing a super resolution image by minimizing degradation from aliasing, noise, and blur. The resulting image has high resolving power, clarity, and a 3D view of the specimen.
This slide is about introduction of blurred image recognition system using legendre's moment invariant algorithm and explain about blurred image will be recognized and converted into original image
Deep Learning - a Path from Big Data Indexing to Robotic ApplicationsDarius Burschka
These are the slides to my ShanghAI lecture from Dec 10, 2020. It proposes necessary extensions to make DeepNets appropriate tools for robotic systems.
The talk can be found on https://fb.watch/2hXDC6K4Pq/
An Assessment of Image Matching Algorithms in Depth EstimationCSCJournals
Computer vision is often used with mobile robot for feature tracking, landmark sensing, and obstacle detection. Almost all high-end robotics systems are now equipped with pairs of cameras arranged to provide depth perception. In stereo vision application, the disparity between the stereo images allows depth estimation within a scene. Detecting conjugate pair in stereo images is a challenging problem known as the correspondence problem. The goal of this research is to assess the performance of SIFT, MSER, and SURF, the well known matching algorithms, in solving the correspondence problem and then in estimating the depth within the scene. The results of each algorithm are evaluated and presented. The conclusion and recommendations for future works, lead towards the improvement of these powerful algorithms to achieve a higher level of efficiency within the scope of their performance.
An Application of Stereo Image Reprojection from Multi-Angle Images fo...Tatsuro Matsubara
This document presents a stereo image reprojection system for immersive virtual reality using images from multiple cameras. The system separates the VR process into rendering images from cameras placed spherically and calculating a view image for display based on head tracking. It develops a method to adjust the interpupillary distance for different head tilts by varying the camera positions. The system is shown to work in real-time on laptops and smartphones using VR headsets to provide an inexpensive way to experience immersive VR. Future work includes optimizing the image size and number of cameras needed.
Image fusion is the process of combining two or more images with specific objects with more precision. It is very common that when one object is focused remaining objects will be less highlighted. To get an image highlighted in all areas, a different means is necessary. This is done by the Image Fusion. In remote sensing, the increasing availability of Space borne images and synthetic aperture radar images gives a motivation to different kinds of image fusion algorithms. In the literature a number of time domain image fusion techniques are available. Few transform domain fusion techniques are proposed. In transform domain fusion techniques, the source images will be decomposed, then integrated into a single data and will be reconstructed back into time domain. In this paper, singular value decomposition as a tool to have transform domain data will be utilized for image fusion. In the literature, the quality assessment of fusion techniques is mainly by subjective tests. In this paper, objective quality assessment metrics are calculated for existing and proposed techniques. It has been found that the new image fusion technique outperformed the existing ones.
IRJET- Robust Edge Detection using Moore’s Algorithm with Median FilterIRJET Journal
The document proposes a robust edge detection method using Moore's algorithm with median filtering. It performs foreground detection on input images to segment the foreground from background. Moore's neighbor algorithm is then used to trace boundaries and detect edges. Median filtering is also applied to remove noise while preserving edges. The method is tested on BSD dataset images and evaluated based on metrics like PSNR, SNR, RMSE, etc. Results show the proposed method performs better edge detection compared to modified Moore's algorithm, Canny Moore, and Sobel Moore approaches.
6 - Conception of an Autonomous UAV using Stereo Vision (presented in an Indo...Youness Lahdili
This document proposes a system for autonomous navigation of unmanned vehicles using stereo vision. It involves three main stages: 1) image rectification to correct distortions, 2) sparse feature detection to select salient image points efficiently, and 3) stereo matching to determine corresponding points between images to perceive depth. The system will be implemented on an FPGA and tested on a drone. It aims to allow drones to autonomously detect and avoid obstacles without human guidance.
This document discusses atmospheric turbulence degraded image restoration using back propagation neural network. It proposes using a feed-forward neural network with 20 hidden layers and one output layer trained with backpropagation to restore images degraded by atmospheric turbulence and noise. The network is trained on normalized input images and tested on blurred images. Results show the proposed method achieves higher PSNR values than other techniques like kurtosis minimization and PCA, indicating better image quality restoration. Future work may incorporate median filtering and using first order image features for network weight assignment.
Interactive Full-Body Motion Capture Using Infrared Sensor Network ijcga
The document describes a new technique for interactive full-body motion capture using multiple infrared sensors. It processes data from each sensor independently and then combines the results to enhance flexibility and accuracy. The method aims to maintain real-time performance while improving on issues like limited actor orientation, inaccurate joint tracking, and conflicting data from individual sensors.
Real-time 3D Object Pose Estimation and Tracking for Natural Landmark Based V...c.choi
1) The document describes a real-time method for estimating and tracking the 3D pose of a rigid object using either a mono or stereo camera.
2) The method combines scale invariant feature matching (SIFT) for initial pose estimation with optical flow-based tracking (KLT) for efficient local pose estimation.
3) Outliers in the tracking are removed using RANSAC to improve accuracy, and tracking restarts from initial pose estimation if the number of inliers falls below a threshold.
This document summarizes a research paper that studied the application of compressed sensing techniques to magnetic resonance imaging (MRI). It conducted simulations in MATLAB to show how sparsity of MRI signals can be exploited to accurately reconstruct images from far fewer measurements. The simulations used two MRI knee images and compared reconstruction with different sampling methods and parameters. Results demonstrated that compressed sensing enables accurate reconstruction from highly undersampled data, requiring around 4-5 times fewer measurements than the signal sparsity. This reduction in measurements can significantly decrease MRI scan times while maintaining image quality.
Interactive full body motion capture using infrared sensor networkijcga
Traditional motion capture (mocap) has been
well
-
stud
ied in visual science for
the last decades
. However
the fie
ld is mostly about capturing
precise animation to be used in
specific
application
s
after
intensive
post
processing such as studying biomechanics or rigging models in movies. These data set
s are normally
captured in complex laboratory environments with
sophisticated
equipment thus making motion capture a
field that is mostly exclusive to professional animators.
In
addition
, obtrusive sensors must be attached to
actors and calibrated within t
he capturing system, resulting in limited and unnatural motion.
In recent year
the rise of computer vision and interactive entertainment opened the gate for a different type of motion
capture which focuses on producing
optical
marker
less
or mechanical sens
orless
motion capture.
Furtherm
ore a wide array of low
-
cost
device are released that are easy to use
for less mission critical
applications
.
This paper
describe
s
a new technique of using multiple infrared devices to process data from
multiple infrared sensors to enhance the flexibility and accuracy of the markerless mocap
using commodity
devices such as Kinect
. The method involves analyzing each individual sensor
data, decompose and rebuild
them into a uniformed skeleton across all sensors. We then assign criteria to define the confidence level of
captured signal from
sensor. Each sensor operates on its own process and communicates through MPI.
Our method emphasize
s on the need of minimum calculation overhead for better real time performance
while being able to maintain good scalability
Passive techniques for detection of tampering in images by Surbhi Arora and S...arorasurbhi
This document summarizes research on passive techniques for detecting tampering in digital images. It discusses common types of tampering like copy-paste and describes approaches using rule-based and training-based methods. For rule-based, it evaluates exact match, robust match, and SURF features techniques. For training-based, it trains SVMs on block intensities, DWT/DFT moments, and SURF features. Testing showed the combination of Hu moments and block intensity had highest accuracy. While rule-based is not dependent on training data, training-based can detect more transformations but depends on training data quality and quantity. Future work involves improving rule-based for noise and SURF segmentation and adding more training images
The document describes mobile GPS tracking. It discusses the requirements for a GPS tracking system including functional requirements like user creation, track creation, sending GPS coordinates to a server, and following tracks in real-time. It also covers non-functional requirements, software requirements including the application server, database, and mobile application. The design section describes the architecture, components, and modules of the system including entity beans, JSPs, servlets, and the mobile application. It also discusses communication between modules and provides use case diagrams. The integration and testing section describes the testing methodology and provides examples of unit test cases.
This document discusses how information and communication technologies (ICT) are enabling a "quantum leap" in Africa's development. It describes ICT's potential to reach communities, provide economic opportunities, and reduce social and geographic barriers. Examples are given from the 2007 World Information Technology Forum for Africa, showing multi-stakeholder projects using ICT in areas like agriculture, education, health, and e-government. The International Federation for Information Processing's role in convening stakeholders to discuss ICT policies and share experiences is also outlined. While challenges remain around follow-through, partnerships, and policy harmonization, increasing cooperation and practical implementations of commitments show promise for ICT to significantly advance Africa's development.
The Machine Vision and Perception Group at the Technical University of Munich conducts research on visual perception and its application to medical, mobile, and human-computer interaction systems. This includes areas like registration of rigid and deformable objects, monocular reconstruction, visual localization and mapping, and biologically inspired navigation and action analysis. The group develops algorithms for tasks like 3D object recognition in point clouds that are robust to incomplete and noisy data.
This document describes a study that used the curvelets transform method to identify abnormalities in MRI images. It begins with an abstract that outlines using curvelets to analyze different MRI image formats and calculate metrics like mean squared error and peak signal-to-noise ratio to evaluate image quality. The document then provides background on curvelets, wavelets, discrete wavelet transforms, and other digital image processing concepts. It describes applying curvelets and other methods to segment MRI images and identify abnormalities. The document presents results of applying curvelets versus other methods to several MRI images and concludes that curvelets provided more accurate and significant results for frequency and time representation with higher quality than older wavelet-based methods.
Heap graph, software birthmark, frequent sub graph mining.iosrjce
IOSR Journal of Computer Engineering (IOSR-JCE) is a double blind peer reviewed International Journal that provides rapid publication (within a month) of articles in all areas of computer engineering and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications in computer technology. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
Autonomous Path Planning and Navigation of a Mobile Robot with Multi-Sensors ...CSCJournals
The mobile robot is applied widely and investigated deeply in industrial fields, meanwhile, mobile robot autonomous path planning and navigation algorithm is a hot research topic. In this paper, firstly mobile robot is introduced, the general path planning and navigation algorithms of the mobile robot are reviewed, then a fuzzy logic with filter smoothing is proposed based on the data from the laser scan sensor and GPS module, which is useful for mobile robot to find the best path to the destination automatically according to the position and size of the gaps between the obstacles in the dynamic environment, finally our designed mobile robot and corresponding Android APP are introduced, the path planning and navigation algorithms are tested on this mobile robot, the testing result shows that this algorithm is globally optimized, quickly responded, battery power and hardware cost saved compared with other algorithms, it is suitable for the mobile robot that is running on the embedded system and it can satisfy our design requirement.
The document proposes a hybrid approach for segmenting brain tumors in MRI images using wavelet and watershed transforms. It begins with applying wavelet transform to produce approximation and detail images for noise reduction. Edge detection is then performed on the approximation image. Watershed transform is applied for initial segmentation at low resolution. Repeated inverse wavelet transform is used to increase the segmented image resolution. Region merging is applied for further segmentation refinement before cropping the tumor area. The results show this coactive wavelet-watershed approach can help achieve accurate tumor segmentation.
Super resolution imaging using frequency wavelets and three dimensionalIAEME Publication
This document describes a method for achieving super resolution imaging using frequency wavelets and three-dimensional views with holographic technique. The method involves three main steps: 1) Registering low resolution images taken of the same specimen from different angles using digital holographic equipment to determine sub-pixel shifts between images; 2) Performing interpolation using frequency wavelet methods to increase resolution and add high frequency information; 3) Reconstructing a super resolution image by minimizing degradation from aliasing, noise, and blur. The resulting image has high resolving power, clarity, and a 3D view of the specimen.
This slide is about introduction of blurred image recognition system using legendre's moment invariant algorithm and explain about blurred image will be recognized and converted into original image
Deep Learning - a Path from Big Data Indexing to Robotic ApplicationsDarius Burschka
These are the slides to my ShanghAI lecture from Dec 10, 2020. It proposes necessary extensions to make DeepNets appropriate tools for robotic systems.
The talk can be found on https://fb.watch/2hXDC6K4Pq/
An Assessment of Image Matching Algorithms in Depth EstimationCSCJournals
Computer vision is often used with mobile robot for feature tracking, landmark sensing, and obstacle detection. Almost all high-end robotics systems are now equipped with pairs of cameras arranged to provide depth perception. In stereo vision application, the disparity between the stereo images allows depth estimation within a scene. Detecting conjugate pair in stereo images is a challenging problem known as the correspondence problem. The goal of this research is to assess the performance of SIFT, MSER, and SURF, the well known matching algorithms, in solving the correspondence problem and then in estimating the depth within the scene. The results of each algorithm are evaluated and presented. The conclusion and recommendations for future works, lead towards the improvement of these powerful algorithms to achieve a higher level of efficiency within the scope of their performance.
An Application of Stereo Image Reprojection from Multi-Angle Images fo...Tatsuro Matsubara
This document presents a stereo image reprojection system for immersive virtual reality using images from multiple cameras. The system separates the VR process into rendering images from cameras placed spherically and calculating a view image for display based on head tracking. It develops a method to adjust the interpupillary distance for different head tilts by varying the camera positions. The system is shown to work in real-time on laptops and smartphones using VR headsets to provide an inexpensive way to experience immersive VR. Future work includes optimizing the image size and number of cameras needed.
Image fusion is the process of combining two or more images with specific objects with more precision. It is very common that when one object is focused remaining objects will be less highlighted. To get an image highlighted in all areas, a different means is necessary. This is done by the Image Fusion. In remote sensing, the increasing availability of Space borne images and synthetic aperture radar images gives a motivation to different kinds of image fusion algorithms. In the literature a number of time domain image fusion techniques are available. Few transform domain fusion techniques are proposed. In transform domain fusion techniques, the source images will be decomposed, then integrated into a single data and will be reconstructed back into time domain. In this paper, singular value decomposition as a tool to have transform domain data will be utilized for image fusion. In the literature, the quality assessment of fusion techniques is mainly by subjective tests. In this paper, objective quality assessment metrics are calculated for existing and proposed techniques. It has been found that the new image fusion technique outperformed the existing ones.
IRJET- Robust Edge Detection using Moore’s Algorithm with Median FilterIRJET Journal
The document proposes a robust edge detection method using Moore's algorithm with median filtering. It performs foreground detection on input images to segment the foreground from background. Moore's neighbor algorithm is then used to trace boundaries and detect edges. Median filtering is also applied to remove noise while preserving edges. The method is tested on BSD dataset images and evaluated based on metrics like PSNR, SNR, RMSE, etc. Results show the proposed method performs better edge detection compared to modified Moore's algorithm, Canny Moore, and Sobel Moore approaches.
6 - Conception of an Autonomous UAV using Stereo Vision (presented in an Indo...Youness Lahdili
This document proposes a system for autonomous navigation of unmanned vehicles using stereo vision. It involves three main stages: 1) image rectification to correct distortions, 2) sparse feature detection to select salient image points efficiently, and 3) stereo matching to determine corresponding points between images to perceive depth. The system will be implemented on an FPGA and tested on a drone. It aims to allow drones to autonomously detect and avoid obstacles without human guidance.
This document discusses atmospheric turbulence degraded image restoration using back propagation neural network. It proposes using a feed-forward neural network with 20 hidden layers and one output layer trained with backpropagation to restore images degraded by atmospheric turbulence and noise. The network is trained on normalized input images and tested on blurred images. Results show the proposed method achieves higher PSNR values than other techniques like kurtosis minimization and PCA, indicating better image quality restoration. Future work may incorporate median filtering and using first order image features for network weight assignment.
Interactive Full-Body Motion Capture Using Infrared Sensor Network ijcga
The document describes a new technique for interactive full-body motion capture using multiple infrared sensors. It processes data from each sensor independently and then combines the results to enhance flexibility and accuracy. The method aims to maintain real-time performance while improving on issues like limited actor orientation, inaccurate joint tracking, and conflicting data from individual sensors.
Real-time 3D Object Pose Estimation and Tracking for Natural Landmark Based V...c.choi
1) The document describes a real-time method for estimating and tracking the 3D pose of a rigid object using either a mono or stereo camera.
2) The method combines scale invariant feature matching (SIFT) for initial pose estimation with optical flow-based tracking (KLT) for efficient local pose estimation.
3) Outliers in the tracking are removed using RANSAC to improve accuracy, and tracking restarts from initial pose estimation if the number of inliers falls below a threshold.
This document summarizes a research paper that studied the application of compressed sensing techniques to magnetic resonance imaging (MRI). It conducted simulations in MATLAB to show how sparsity of MRI signals can be exploited to accurately reconstruct images from far fewer measurements. The simulations used two MRI knee images and compared reconstruction with different sampling methods and parameters. Results demonstrated that compressed sensing enables accurate reconstruction from highly undersampled data, requiring around 4-5 times fewer measurements than the signal sparsity. This reduction in measurements can significantly decrease MRI scan times while maintaining image quality.
Interactive full body motion capture using infrared sensor networkijcga
Traditional motion capture (mocap) has been
well
-
stud
ied in visual science for
the last decades
. However
the fie
ld is mostly about capturing
precise animation to be used in
specific
application
s
after
intensive
post
processing such as studying biomechanics or rigging models in movies. These data set
s are normally
captured in complex laboratory environments with
sophisticated
equipment thus making motion capture a
field that is mostly exclusive to professional animators.
In
addition
, obtrusive sensors must be attached to
actors and calibrated within t
he capturing system, resulting in limited and unnatural motion.
In recent year
the rise of computer vision and interactive entertainment opened the gate for a different type of motion
capture which focuses on producing
optical
marker
less
or mechanical sens
orless
motion capture.
Furtherm
ore a wide array of low
-
cost
device are released that are easy to use
for less mission critical
applications
.
This paper
describe
s
a new technique of using multiple infrared devices to process data from
multiple infrared sensors to enhance the flexibility and accuracy of the markerless mocap
using commodity
devices such as Kinect
. The method involves analyzing each individual sensor
data, decompose and rebuild
them into a uniformed skeleton across all sensors. We then assign criteria to define the confidence level of
captured signal from
sensor. Each sensor operates on its own process and communicates through MPI.
Our method emphasize
s on the need of minimum calculation overhead for better real time performance
while being able to maintain good scalability
Passive techniques for detection of tampering in images by Surbhi Arora and S...arorasurbhi
This document summarizes research on passive techniques for detecting tampering in digital images. It discusses common types of tampering like copy-paste and describes approaches using rule-based and training-based methods. For rule-based, it evaluates exact match, robust match, and SURF features techniques. For training-based, it trains SVMs on block intensities, DWT/DFT moments, and SURF features. Testing showed the combination of Hu moments and block intensity had highest accuracy. While rule-based is not dependent on training data, training-based can detect more transformations but depends on training data quality and quantity. Future work involves improving rule-based for noise and SURF segmentation and adding more training images
The document describes mobile GPS tracking. It discusses the requirements for a GPS tracking system including functional requirements like user creation, track creation, sending GPS coordinates to a server, and following tracks in real-time. It also covers non-functional requirements, software requirements including the application server, database, and mobile application. The design section describes the architecture, components, and modules of the system including entity beans, JSPs, servlets, and the mobile application. It also discusses communication between modules and provides use case diagrams. The integration and testing section describes the testing methodology and provides examples of unit test cases.
This document discusses how information and communication technologies (ICT) are enabling a "quantum leap" in Africa's development. It describes ICT's potential to reach communities, provide economic opportunities, and reduce social and geographic barriers. Examples are given from the 2007 World Information Technology Forum for Africa, showing multi-stakeholder projects using ICT in areas like agriculture, education, health, and e-government. The International Federation for Information Processing's role in convening stakeholders to discuss ICT policies and share experiences is also outlined. While challenges remain around follow-through, partnerships, and policy harmonization, increasing cooperation and practical implementations of commitments show promise for ICT to significantly advance Africa's development.
Innovex aims to merge all improvement projects into the business excellence framework to achieve integration, improve project quality, motivate employee participation in continuous improvement, and create an innovation culture. An award night called Innovex recognizes the best teams for their projects based on return on investment, with over 6000 projects filtered down to 22 winners who are celebrated with their spouses.
Comparing of switching frequency on vector controlled asynchronous motorijscai
Nowadays, asynchronous motors have wide range use in many industrial applications. Field oriented
control (FOC) and direct torque control (DTC) are commonly used methods in high performance vector
control for asynchronous motors. Therefore, it is very important to identify clearly advantages and
disadvantages of both systems in the selection of appropriate control methods for many industrial
applications. This paper aims to present a new and different perspective regarding the comparison of the
switching behaviours on the FOC and the DTC drivers. For this purpose, the experimental studies have
been carried out to compare the inverter switching frequencies and torque responses of the asynchronous
motor in the FOC and the DTC systems under different working conditions. The dSPACE 1103 controller
board was programmed with Matlab/Simulink software. As expected, the experimental studies showed that
the FOC controlled motors has a lessened torque ripple. On the other hand, the FOC controlled motor
switching frequency has about 65-75% more than the DTC controlled under both loaded and unloaded
working conditions
A Prediction Model for Taiwan Tourism Industry Stock Indexijcsit
Investors and scholars pay continuous attention to the stock market, as each day, many investors attempt to
use different methods to predict stock price trends. However, as stock price is affected by economy, politics,
domestic and foreign situations, emergency, human factor, and other unknown factors, it is difficult to
establish an accurate prediction model. This study used a back-propagation neural network (BPN) as the
research approach, and input 29 variables, such as international exchange rate, indices of international
stock markets, Taiwan stock market analysis indicators, and overall economic indicators, to predict
Taiwan’s monthly tourism industry stock index. The empirical findings show that the BPN prediction model
has better predictive accuracy, Absolute Relative Error is 0.090058, and correlation coefficient is
0.944263. The model has low error and high correlation, and can serve as reference for investors and
relevant industries
A CLUSTERING TECHNIQUE FOR EMAIL CONTENT MININGijcsit
In today’s world of internet, with whole lot of e-documents such, as html pages, digital libraries etc. occupying considerable amount of cyber space, organizing these documents has become a practical need. Clustering is an important technique that organizes large number of objects into smaller coherent groups.This helps in efficient and effective use of these documents for information retrieval and other NLP tasks.Email is one of the most frequently used e-document by individual or organization. Email categorization is one of the major tasks of email mining. Categorizing emails into different groups help easy retrieval and maintenance. Like other e-documents, emails can also be classified using clustering algorithms. In this
paper a similarity measure called Similarity Measure for Text Processing is suggested for email clustering.
The suggested similarity measure takes into account three situations: feature appears in both emails, feature appears in only one email and feature appears in none of the emails. The potency of suggested similarity measure is analyzed on Enron email data set to categorize emails. The outcome indicates that the efficiency acquired by the suggested similarity measure is better than that acquired by other measures.
MAP-REDUCE IMPLEMENTATIONS: SURVEY AND PERFORMANCE COMPARISONijcsit
Map Reduce has gained remarkable significance as a rominent parallel data processing tool in the research community, academia and industry with the spurt in volume of data that is to be analyzed. Map Reduce is used in different applications such as data mining, data analytic where massive data analysis is required, but still it is constantly being explored on different parameters such as performance and efficiency. This survey intends to explore large scale data processing using Map Reduce and its various implementations to facilitate the database, researchers and other communities in developing the technical understanding of the Map Reduce framework. In this survey, different Map Reduce implementations are explored and their inherent features are compared on different parameters. It also addresses the open issues and challenges raised on fully functional DBMS/Data Warehouse on Map Reduce. The comparison of various Map Reduce implementations is done with the most popular implementation Hadoop and other similar implementations using other platforms.
Change management and version control of Scientific Applicationsijcsit
The development process of scientific applications is largely dependent on scientific progress and the
experimental research results. Thus, dealing with frequent changes is one of the main problems faced by
the developers of scientific software. Taking into account the results of the survey conducted among
scientists in the HP-SEE project, the implementation of change management and version control software
processes is inevitable. In this paper, we propose software engineering principles that should be included
in the development process to improve the version control and change management. Moreover, we give
some specific recommendations for their implementation, thereby making a slight modification of already
generally accepted templates and methods. The development steps practiced by scientists should not be
replaced completely, but they need to be supplemented with appropriate practices, documents and formal
methods. We also emphasize the reasons for the inclusion of these two processes and the consequences that
may arise as a result of their non-application.
SFAMSS:A S ECURE F RAMEWORK F OR ATM M ACHINES V IA S ECRET S HARINGijcsit
As ATM applications deploy for a banking system, th
e need to secure communications will become critica
l.
However, multicast protocols do not fit the point-t
o-point model of most network security protocols wh
ich
were designed with unicast communications in mind.
In recent years, we have seen the emergence and the
growing of ATMs (Automatic Teller Machines) in bank
ing systems. Many banks are extending their activit
y
and increasing transactions by using ATMs. ATM will
allow them to reach more customers in a cost
effective way and to make their transactions fast a
nd efficient. However, communicating in the network
must satisfy integrity, privacy, confidentiality, a
uthentication and non-repudiation. Many frameworks
have
been implemented to provide security in communicati
on and transactions. In this paper, we analyze ATM
communication protocol and propose a novel framewor
k for ATM systems that allows entities communicate
in a secure way without using a lot of storage. We
describe the architecture and operation of SFAMSS i
n
detail. Our framework is implemented with Java and
the software architecture, and its components are
studied in detailed.
E MOTION I NTERACTION WITH V IRTUAL R EALITY U SING H YBRID E MOTION C...ijcsit
The document describes a new hybrid method for classifying human emotions using electroencephalogram (EEG) brain signals for interaction with virtual reality. The method combines self-assessment, arousal valence dimension modeling, and analysis of variance in brain hemisphere activity. Two basic emotions, happy and sad, are highlighted. EEG signals are used to interpret the user's emotional state. Emotion interaction is expressed through a 3D model changing its walking style based on the classified user emotion. The results show the hybrid method can classify emotions in different circumstances and synchronize a 3D virtual model accordingly. The goal is to develop a new technique for classifying emotions to provide feedback through a 3D virtual character's walking expression.
This document describes a biomodeling software called BioMeteorology that allows users to construct and modify models using various components, run completed models to generate outputs like graphs, tables and maps, and provides a sample model of the lifecycle stages of the white stem borer insect pest. The software contains modules, functions and processes to build models and simulate their outputs.
Portraying Indonesia's Media Power: Election and Political ControlHijjaz Sutriadi
Portraying Indonesia's Media Power: Election and Political Control
A 5-minute presentation material in Media and Information Discussion Group (DG-8) for the 41st Ship for Southeast Asian and Japanese Youth Programme (SSEAYP)
AN INTERESTING APPLICATION OF SIMPLE EXPONENTIAL SMOOTHING IN MUSIC ANALYSISijscai
This document analyzes the structure of the Indian classical raga Bhairavi through simple exponential smoothing. It finds the smoothing factor that best fits the raga's note sequence is 0.481384. It identifies the raga based on its ascent-descent pattern and characteristic note combinations. Melody analysis reveals the most significant melodies in the sequence, with lengths of 12 and 6 notes. The paper concludes the simple exponential model successfully captures the raga's structure and proposes further analyzing other ragas' structures using this and more advanced smoothing techniques.
Data mining model for the data retrieval from central server configurationijcsit
A server, which is to keep track of heavy document traffic, is unable to filter the documents that are most
relevant and updated for continuous text search queries. This paper focuses on handling continuous text
extraction sustaining high document traffic. The main objective is to retrieve recent updated documents
that are most relevant to the query by applying sliding window technique. Our solution indexes the
streamed documents in the main memory with structure based on the principles of inverted file, and
processes document arrival and expiration events with incremental threshold-based method. It also ensures
elimination of duplicate document retrieval using unsupervised duplicate detection. The documents are
ranked based on user feedback and given higher priority for retrieval.
This document provides product details for the St. Augustine Coffee Table from Peters-Revington. The table is made of oak and slate materials with metal legs and costs $566.99. It measures 19" tall by 42" wide by 42" deep and weighs 150 pounds. Reviews praise the table's sturdiness and quality of materials. The St. Augustine collection also includes matching end tables and storage cabinets.
P REPROCESSING FOR PPM: COMPRESSING UTF - 8 ENCODED NATURAL LANG UAGE TEXTijcsit
n this paper,
several new universal preprocessing techniques
are described
to improve Prediction by
Partial Matching (PPM) compression of UTF
-
8 encoded natural language text. These methods essentially
adjust the alphabet in some manner (for exampl
e, by expanding or reducing it) prior to the compression
algorithm then being applied to the amended text.
Firstly,
a simple bigraphs (two
-
byte) substitution
technique
is described
that leads to significant improvement in compression for many languages whe
n they
are encoded by the Unicode scheme (25% for Arabic text, 14% for Armenian,
9% for Persian, 15% for
Russian, 1% for Chinese text, and over 5% for both English and Welsh text)
.
Secondly,
a new
preprocessing technique t
hat outputs separate vocabulary
an
d symbols streams
–
that are subsequently
encoded separately
–
is also investigated
. This also leads to significant improvement in compression for
many languages (24% for Arabic text, 30% for Armenian, 32% for Persian and 35% for Russian). Finally
,
novel p
reprocessing and postprocessing techniques for lossy and lossless text compression of Arabic text
are described for dotted and non
-
dotted forms of the language
P ERFORMANCE M EASUREMENTS OF F EATURE T RACKING AND H ISTOGRAM BASED T ...ijcsit
In this paper, feature tracking based and histogram
based traffic congestion detection systems are
developed. Developed all system are designed to run
as real time application. In this work, ORB (Orien
ted
FAST and Rotated BRIEF) feature extraction method h
ave been used to develop feature tracking based
traffic congestion solution. ORB is a rotation inva
riant, fast and resistant to noise method and conta
ins the
power of FAST and BRIEF feature extraction methods.
Also, two different approaches, which are standard
deviation and weighed average, have been applied to
find out the congestion information by using
histogram of the image to develop histogram based t
raffic congestion solution. Both systems have been
tested on different weather conditions such as clou
dy, sunny and rainy to provide various illumination
at
both daytime and night. For all developed systems p
erformance results are examined to show the
advantages and drawbacks of these systems.
This document summarizes a research paper that presents a method for estimating vehicle acceleration using smartphone sensors. It describes using a quaternion-based unscented Kalman filter to remove the effect of gravity from accelerometer readings, allowing the determination of coordinate acceleration in the vehicle frame of reference. The method involves initializing sensor measurements while stationary, then calculating the orientation of the vehicle relative to the sensor and sensor relative to earth to transform acceleration readings into the vehicle frame.
Stereo Vision Human Motion Detection and Tracking in Uncontrolled EnvironmentTELKOMNIKA JOURNAL
Stereo vision in detecting human motion is an emerging research for automation, robotics, and sports science field due to the advancement of imaging sensors and information technology. The difficulty of human motion detection and tracking is relatively complex when it is applied to uncontrolled environment. In this paper, a hybrid filter approach is proposed to detect human motion in the stereo vision. The hybrid filter approach integrates Gaussian filter and median filter to reduce the coverage of shadow and sudden change of illumination. In addition, sequential thinning and thickening morphological method is used to construct the skeleton model. The proposed hybrid approach is compared with the normalized filter. As a result, the proposed approach produces better skeleton model with less influential effect on shadow and illumination. The output results of the proposed approach can show up to 86% of average accuracy matched with skeleton model. In addition, obtains approximately 94% of sensitivity measurement in the stereo vision. The proposed approach using hybrid filter and sequential morphology could improve the performance of the detection in the uncontrolled environment.
Performance of Various Order Statistics Filters in Impulse and Mixed Noise Re...sipij
Remote sensing images (ranges from satellite to seismic) are affected by number of noises like interference, impulse and speckle noises. Image denoising is one of the traditional problems in digital image processing, which plays vital role as a pre-processing step in number of image and video applications. Image denoising still remains a challenging research area for researchers because noise
removal introduces artifacts and causes blurring of the images. This study is done with the intension of designing a best algorithm for impulsive noise reduction in an industrial environment. A review of the typical impulsive noise reduction systems which are based on order statistics are done and particularized for the described situation. Finally, computational aspects are analyzed in terms of PSNR values and some solutions are proposed.
Leader Follower Formation Control of Ground Vehicles Using Dynamic Pixel Coun...ijma
This paper deals with leader-follower formations of non-holonomic mobile robots, introducing a formation
control strategy based on pixel counts using a commercial grade electro optics camera. Localization of the
leader for motions along line of sight as well as the obliquely inclined directions are considered based on
pixel variation of the images by referencing to two arbitrarily designated positions in the image frames.
Based on an established relationship between the displacement of the camera movement along the viewing
direction and the difference in pixel counts between reference points in the images, the range and the angle
estimate between the follower camera and the leader is calculated. The Inverse Perspective Transform is
used to account for non linear relationship between the height of vehicle in a forward facing image and its
distance from the camera. The formulation is validated with experiments.
iaetsd Image fusion of brain images using discrete wavelet transformIaetsd Iaetsd
1) The document discusses using discrete wavelet transform to fuse MRI and CT brain images. This allows physicians to view soft tissue details from MRI and bone details from CT in a single fused image.
2) Discrete wavelet transform decomposes images into different frequency bands, allowing salient features like edges to be separated. It is proposed to fuse MRI and CT brain images using discrete wavelet transform to reduce noise and computational load compared to other methods.
3) Fusing the images provides advantages for physicians by having both soft tissue and bone details in a single image, reducing storage costs compared to viewing images separately.
The document discusses different types of motion capture systems including optical, non-optical, and facial motion capture systems. Optical systems use cameras and markers to calculate 3D positions. Non-optical systems include inertial systems using sensors, mechanical systems using exoskeletons, and magnetic systems tracking magnetic fields. Facial motion capture aims to record complex facial movements. Motion capture technology is used in entertainment, sports, medical applications, and robotics research.
This document summarizes an experiment that tested optical flow-based navigation using a robot equipped with a webcam. Motion detection filters like correlation and Gabor filters were developed and applied to image sequences to detect optical flow. The filters were implemented in optical flow navigation programs for an iRobot robot. The robot was able to navigate a textured environment but struggled with obstacles and corners. Future work could include faster computation using GPUs or wider field of view cameras to improve navigation abilities.
This paper describes a decision tree (DT) based pedometer algorithm and its implementation on
Android. The DT- based pedometer can classify 3 gait patterns, including walking on level
ground (WLG), up stairs (WUS) and down stairs (WDS). It can discard irrelevant motion and
count user’s steps accurately. The overall classification accuracy is 89.4%. Accelerometer,
gyroscope and magnetic field sensors are used in the device. When user puts his/her smart
phone into the pocket, the pedometer can automatically count steps of different gait patterns.
Two methods are tested to map the acceleration from mobile phone’s reference frame to the
direction of gravity. Two significant features are employed to classify different gait patterns.
The document proposes a framework that uses intelligent mobile devices to enable indoor wireless location tracking, navigation, and mobile augmented reality (AR). It discusses using mobile devices equipped with inertial measurement units (IMU) and multi-touch screens to provide user feedback to correct positioning errors. The framework also uses mobile AR through device cameras to help navigate users in complex 3D indoor environments and provide interactive location-based services. A prototype system was developed to demonstrate the feasibility of the proposed application framework.
This document summarizes a research paper on detecting and tracking human motion based on background subtraction. The proposed method initializes the background using the median of multiple frames. It then extracts moving objects by subtracting the current frame from the background and applying a dynamic threshold. Noise is removed using filters and morphology operations. Shadows are accounted for using projection analysis to accurately detect human bodies. Tracking involves computing the centroid of detected objects in each frame to analyze position and velocity over time. Experimental results showed the method runs quickly and accurately for real-time detection of human motion.
A VLSI Architecture Realisation of an Wireless Endoscopy Systemijesajournal
The main objective is to design a VLSI architecture to realize an wireless endoscopy system. This system is
used in medicinal field by recording images of the digestive system. It is developed to transfer the image data
using the RF transmission so as to avoid the pain and irritation to the digestive tract which can be caused by
the cables when using conventional endoscopes. The proposed system consists of a RF transceiver and a
CMOS color image sensor. Capturing of images is done by image color sensor. RF transceiver is used to
send the images wirelessly. CMOS color image sensor is interfaced with FPGA. Real time images captured
by the color image sensor are compressed and they are sent wirelessly by the RF transceiver. Image
compression is used since it is the best way to save the power in transmission and reception and to decrease
the bandwidth in communication. So, after capturing the image using the CMOS color image sensor, the
image is compressed. Compression is done by JPEG standard. After high-quality lossy compression, the
image is transmitted by the wireless RF transceiver. Wireless transceiver is chosen in such a way that it is
operated in low power.
Enhanced Algorithm for Obstacle Detection and Avoidance Using a Hybrid of Pla...IOSR Journals
This document presents an enhanced algorithm for obstacle detection and avoidance using a hybrid of plane-to-plane homography, image segmentation, corner detection, and edge detection techniques. The algorithm aims to improve upon previous methods by eliminating false positives, reducing unreliable corners and broken edges, providing depth perception without planar assumptions, and requiring less processing power. The key components of the algorithm include plane-to-plane homography, image segmentation, Canny edge detection, Harris corner detection, and the RANSAC sampling method for system analysis. Test results on sample images show the algorithm can accurately detect obstacles based on texture differences while reducing noise from ground plane textures.
This document describes a method for indoor localization using a smartphone and Bluetooth Low Energy (BLE) sensor tag. The sensor tag contains an accelerometer, gyroscope, and other sensors to measure a user's motion and transmit the data via BLE to a smartphone app. The app uses dead reckoning algorithms integrating accelerometer and gyroscope data to calculate the user's distance and direction of movement over time without GPS or network connectivity. Challenges included increasing the sensor sampling rate and integrating data from multiple sensors. The described method provides indoor navigation when outdoor positioning systems like GPS are unavailable.
Indoor localisation and dead reckoning using Sensor Tag™ BLE.Abhishek Madav
The mobile application uses readings of the Accelerometer and Gyroscope from the Sensor Tag to describe details of motion in a planar mode. The project has been implemented as a part of the EECS 221 coursework at University of California, Irvine.
This document describes a method for indoor localization using a smartphone and Bluetooth Low Energy (BLE) sensor tag. The sensor tag contains an accelerometer, gyroscope, and other sensors to measure a user's motion and transmit the sensor data via BLE to a smartphone app. The app uses dead reckoning algorithms integrating accelerometer and gyroscope data to calculate the user's distance and direction of movement over time without GPS or network connectivity. Challenges addressed include increasing the sensor sampling rate and integrating accelerometer and gyroscope data to limit position error accumulation. The described system provides indoor navigation when outdoor positioning systems like GPS are unavailable.
Automatic License Plate Detection in Foggy Condition using Enhanced OTSU Tech...IRJET Journal
This document presents research on detecting license plates in foggy conditions using an enhanced OTSU technique. The researchers tested their technique on a large database of license plate images taken under different conditions, including clear and foggy images. They evaluated the technique using various performance parameters such as MSE, PSNR, SSIM, and aspect ratio. When compared to a base technique, the enhanced OTSU technique showed improvements in these parameters of 14.93%, 14.12%, 39.21%, and 40% respectively. The technique aims to better handle hazardous image conditions like foggy weather that existing techniques often struggle with. It uses steps like image denoising, thresholding segmentation, and character extraction to read license plates in low-visibility situations
Review on vibration analysis with digital image processingIAEME Publication
This document summarizes research on analyzing vibrations using digital image processing. It discusses using cameras to capture images of vibrating plates and analyzing the images using algorithms to determine resonant frequencies and mode shapes. MATLAB is used for the image processing and analysis. The document reviews several related studies on using techniques like electronic speckle pattern interferometry to characterize vibrations of plates and structures non-contact. It also presents a case study on using digital image processing to characterize the vibration of a tuning fork by measuring its amplitude response over different excitation frequencies.
GPS & GSM based Voice Alert System for Blind Personijsrd.com
This paper presents a theoretical model and a system concept to provide a smart electronic aid for blind people. This system is intended to provide overall measures –object detection and real time assistance via Global Positioning System (GPS).The system consist of ultrasonic sensor, GPS Module, GSM Module and vibratory circuit (speakers or head phones). This project aims at the development of an Electronic Travelling Aid (ETA) kit to help the blind people to find obstacle free path. This ETA is fixed to the stick of the blind people. When the object is detected near to the blinds stick it alerts them with the help of vibratory circuit (speakers or head phones). The location of the blind is found using Global System for Mobile communications (GSM) and Global Position System (GPS).
Motion capture is the process of recording movements of humans or objects and translating that data into digital form that can be used in films, games, and other media. It works by tracking markers placed on actors' bodies and using multiple synchronized cameras to triangulate the 3D positions over time. Early motion capture used mechanical exoskeletons connected to joints, but modern optical systems track passive reflective markers with cameras in the infrared spectrum. Optical motion capture is now commonly used in film production due to its accuracy and ability to capture complex performances without wires or sensors restricting movement.
Similar to GPS Tracking System Coupled With Image Processing In Traffic Signals to Enhance Life Security (20)
Trusted Execution Environment for Decentralized Process MiningLucaBarbaro3
Presentation of the paper "Trusted Execution Environment for Decentralized Process Mining" given during the CAiSE 2024 Conference in Cyprus on June 7, 2024.
5th LF Energy Power Grid Model Meet-up SlidesDanBrown980551
5th Power Grid Model Meet-up
It is with great pleasure that we extend to you an invitation to the 5th Power Grid Model Meet-up, scheduled for 6th June 2024. This event will adopt a hybrid format, allowing participants to join us either through an online Mircosoft Teams session or in person at TU/e located at Den Dolech 2, Eindhoven, Netherlands. The meet-up will be hosted by Eindhoven University of Technology (TU/e), a research university specializing in engineering science & technology.
Power Grid Model
The global energy transition is placing new and unprecedented demands on Distribution System Operators (DSOs). Alongside upgrades to grid capacity, processes such as digitization, capacity optimization, and congestion management are becoming vital for delivering reliable services.
Power Grid Model is an open source project from Linux Foundation Energy and provides a calculation engine that is increasingly essential for DSOs. It offers a standards-based foundation enabling real-time power systems analysis, simulations of electrical power grids, and sophisticated what-if analysis. In addition, it enables in-depth studies and analysis of the electrical power grid’s behavior and performance. This comprehensive model incorporates essential factors such as power generation capacity, electrical losses, voltage levels, power flows, and system stability.
Power Grid Model is currently being applied in a wide variety of use cases, including grid planning, expansion, reliability, and congestion studies. It can also help in analyzing the impact of renewable energy integration, assessing the effects of disturbances or faults, and developing strategies for grid control and optimization.
What to expect
For the upcoming meetup we are organizing, we have an exciting lineup of activities planned:
-Insightful presentations covering two practical applications of the Power Grid Model.
-An update on the latest advancements in Power Grid -Model technology during the first and second quarters of 2024.
-An interactive brainstorming session to discuss and propose new feature requests.
-An opportunity to connect with fellow Power Grid Model enthusiasts and users.
TrustArc Webinar - 2024 Global Privacy SurveyTrustArc
How does your privacy program stack up against your peers? What challenges are privacy teams tackling and prioritizing in 2024?
In the fifth annual Global Privacy Benchmarks Survey, we asked over 1,800 global privacy professionals and business executives to share their perspectives on the current state of privacy inside and outside of their organizations. This year’s report focused on emerging areas of importance for privacy and compliance professionals, including considerations and implications of Artificial Intelligence (AI) technologies, building brand trust, and different approaches for achieving higher privacy competence scores.
See how organizational priorities and strategic approaches to data security and privacy are evolving around the globe.
This webinar will review:
- The top 10 privacy insights from the fifth annual Global Privacy Benchmarks Survey
- The top challenges for privacy leaders, practitioners, and organizations in 2024
- Key themes to consider in developing and maintaining your privacy program
GraphRAG for Life Science to increase LLM accuracyTomaz Bratanic
GraphRAG for life science domain, where you retriever information from biomedical knowledge graphs using LLMs to increase the accuracy and performance of generated answers
Ocean lotus Threat actors project by John Sitima 2024 (1).pptxSitimaJohn
Ocean Lotus cyber threat actors represent a sophisticated, persistent, and politically motivated group that poses a significant risk to organizations and individuals in the Southeast Asian region. Their continuous evolution and adaptability underscore the need for robust cybersecurity measures and international cooperation to identify and mitigate the threats posed by such advanced persistent threat groups.
Introduction of Cybersecurity with OSS at Code Europe 2024Hiroshi SHIBATA
I develop the Ruby programming language, RubyGems, and Bundler, which are package managers for Ruby. Today, I will introduce how to enhance the security of your application using open-source software (OSS) examples from Ruby and RubyGems.
The first topic is CVE (Common Vulnerabilities and Exposures). I have published CVEs many times. But what exactly is a CVE? I'll provide a basic understanding of CVEs and explain how to detect and handle vulnerabilities in OSS.
Next, let's discuss package managers. Package managers play a critical role in the OSS ecosystem. I'll explain how to manage library dependencies in your application.
I'll share insights into how the Ruby and RubyGems core team works to keep our ecosystem safe. By the end of this talk, you'll have a better understanding of how to safeguard your code.
Ivanti’s Patch Tuesday breakdown goes beyond patching your applications and brings you the intelligence and guidance needed to prioritize where to focus your attention first. Catch early analysis on our Ivanti blog, then join industry expert Chris Goettl for the Patch Tuesday Webinar Event. There we’ll do a deep dive into each of the bulletins and give guidance on the risks associated with the newly-identified vulnerabilities.
In the rapidly evolving landscape of technologies, XML continues to play a vital role in structuring, storing, and transporting data across diverse systems. The recent advancements in artificial intelligence (AI) present new methodologies for enhancing XML development workflows, introducing efficiency, automation, and intelligent capabilities. This presentation will outline the scope and perspective of utilizing AI in XML development. The potential benefits and the possible pitfalls will be highlighted, providing a balanced view of the subject.
We will explore the capabilities of AI in understanding XML markup languages and autonomously creating structured XML content. Additionally, we will examine the capacity of AI to enrich plain text with appropriate XML markup. Practical examples and methodological guidelines will be provided to elucidate how AI can be effectively prompted to interpret and generate accurate XML markup.
Further emphasis will be placed on the role of AI in developing XSLT, or schemas such as XSD and Schematron. We will address the techniques and strategies adopted to create prompts for generating code, explaining code, or refactoring the code, and the results achieved.
The discussion will extend to how AI can be used to transform XML content. In particular, the focus will be on the use of AI XPath extension functions in XSLT, Schematron, Schematron Quick Fixes, or for XML content refactoring.
The presentation aims to deliver a comprehensive overview of AI usage in XML development, providing attendees with the necessary knowledge to make informed decisions. Whether you’re at the early stages of adopting AI or considering integrating it in advanced XML development, this presentation will cover all levels of expertise.
By highlighting the potential advantages and challenges of integrating AI with XML development tools and languages, the presentation seeks to inspire thoughtful conversation around the future of XML development. We’ll not only delve into the technical aspects of AI-powered XML development but also discuss practical implications and possible future directions.
Fueling AI with Great Data with Airbyte WebinarZilliz
This talk will focus on how to collect data from a variety of sources, leveraging this data for RAG and other GenAI use cases, and finally charting your course to productionalization.
HCL Notes und Domino Lizenzkostenreduzierung in der Welt von DLAUpanagenda
Webinar Recording: https://www.panagenda.com/webinars/hcl-notes-und-domino-lizenzkostenreduzierung-in-der-welt-von-dlau/
DLAU und die Lizenzen nach dem CCB- und CCX-Modell sind für viele in der HCL-Community seit letztem Jahr ein heißes Thema. Als Notes- oder Domino-Kunde haben Sie vielleicht mit unerwartet hohen Benutzerzahlen und Lizenzgebühren zu kämpfen. Sie fragen sich vielleicht, wie diese neue Art der Lizenzierung funktioniert und welchen Nutzen sie Ihnen bringt. Vor allem wollen Sie sicherlich Ihr Budget einhalten und Kosten sparen, wo immer möglich. Das verstehen wir und wir möchten Ihnen dabei helfen!
Wir erklären Ihnen, wie Sie häufige Konfigurationsprobleme lösen können, die dazu führen können, dass mehr Benutzer gezählt werden als nötig, und wie Sie überflüssige oder ungenutzte Konten identifizieren und entfernen können, um Geld zu sparen. Es gibt auch einige Ansätze, die zu unnötigen Ausgaben führen können, z. B. wenn ein Personendokument anstelle eines Mail-Ins für geteilte Mailboxen verwendet wird. Wir zeigen Ihnen solche Fälle und deren Lösungen. Und natürlich erklären wir Ihnen das neue Lizenzmodell.
Nehmen Sie an diesem Webinar teil, bei dem HCL-Ambassador Marc Thomas und Gastredner Franz Walder Ihnen diese neue Welt näherbringen. Es vermittelt Ihnen die Tools und das Know-how, um den Überblick zu bewahren. Sie werden in der Lage sein, Ihre Kosten durch eine optimierte Domino-Konfiguration zu reduzieren und auch in Zukunft gering zu halten.
Diese Themen werden behandelt
- Reduzierung der Lizenzkosten durch Auffinden und Beheben von Fehlkonfigurationen und überflüssigen Konten
- Wie funktionieren CCB- und CCX-Lizenzen wirklich?
- Verstehen des DLAU-Tools und wie man es am besten nutzt
- Tipps für häufige Problembereiche, wie z. B. Team-Postfächer, Funktions-/Testbenutzer usw.
- Praxisbeispiele und Best Practices zum sofortigen Umsetzen
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GPS Tracking System Coupled With Image Processing In Traffic Signals to Enhance Life Security
1. International Journal of Computer Science & Information Technology (IJCSIT) Vol 5, No 4, August 2013
DOI : 10.5121/ijcsit.2013.5410 131
GPS Tracking System Coupled With Image
Processing In Traffic Signals to Enhance Life
Security
Manoj Prabhakar K 1
and Manoj Kumar S 2
1
Anna University, Chennai, India
manojkrishs@gmail.com
2
Anna University, Chennai, India
manojkumars.msec@gmail.com
ABSTRACT
In modern and crowded traffic life, it becomes mandatory to save the human life by reaching the hospital
very sooner than possible. This paper explains about the advancement in tracking the ambulance presence
amidst the traffic with the usage of GPS tracking system calculating the position of the ambulance from the
traffic signal which replaces the RF transmitter receiver circuitry. This paper also retains the use of the
image capturing technology available from the base paper (IMPACT OF IMAGE PROCESSING IN
SAVING THE HUMAN LIFE BY AUTOMATING TRAFFIC SIGNALS) to identify the presence of the
ambulance, thereby changing the signal to green automatically in favour of ambulance.
KEYWORDS
Image Processing, Trigger, Ambulance, Human Life, Ambulance GPS Tracking system, Ambulance
position, Proximity sensors.
1. INTRODUCTION
An image is nothing but the subset of signal. Generally a signal is used to convey the information
from one end to other end. These sorts of signals can be used in many ways. Electrical signals are
used in television, radio, etc, which is transmitted by electrical quantities. Here the digital
processing is the process of extracting information from the signals. Every signal will have
certain information which is to be transmitted to the other end.
The digital signal processing is mainly related representing and processing of the numbers
(sequence) and symbols. The signals have many characteristics such as its shapes, time durations,
amplitudes and etc. These signals can be classified as continuous and discrete time signals based
on sampling. There are two types of signals, analog and digital signals. If the signals are repeating
after some period, they are called periodic signals. Every signal can be fixed by Mathematical
functions. The signals are classified into three types according to its dimensions. They are 1D
(One-Dimensional), 2D (Two-Dimensional), 3D (Three-Dimensional).
The One Dimensional signals will be using time waveforms x(t) or f(t). Two dimensional signals
will be used two axis such as (x,y) 2D signals are the function of two independent variables called
as (x,y) and has been projected in x,y plane. The 2D signals will be projecting the images and still
2. International Journal of Computer Science & Information Technology (IJCSIT) Vol 5, No 4, August 2013
132
photographs. The Three dimensional signals will be plotted in (x,y,z) plane. It represents the
images in sequences and in dynamic manner, which in turn called as video signals.
Here, we are using the digital image processing to transmit signals to traffic signals and thereby
triggering the signal to green for ambulances. This can be done by using the placing the motion
camera in all traffic signals, which captures the video signals and when there in ambulance in the
road, it automatically changes the signal green according to the speed and time where ambulance
has been placed. Also, as an improvement of the previous project GPS tracking system will be
used this time to track the position of the ambulance. Since, all the traffic signals are monitored
and will be automated in the near future; every ambulance will be tracked with the help of the
GPS systems. The GPS systems will use the Geographic map information of the area along with
the live position data from GPS based vehicle tracking unit installed in the Ambulance, and
presents the same on a traffic control station. This will automate the signal to green based on the
geographical location of the ambulance. The GPS system can also guide the ambulance to the
accident location as well based on the position of the nearest ambulance and accident location.
Every ambulance will be attached with a proximity sensor device which emit the signals in
particular frequencies to the proximity receiver that has been placed in traffic signals. The
receiver that has been placed in the traffic signals will receive the signals transmitted by
ambulance based on the approach speed of the ambulance. In this paper, we will be discussing
about how the images will be recognized and how the signals will be transmitted and received.
In order to provide the clear image we will be using smoothing filter and sharpening filter which
reduce the distortion and interference while capturing the images and in order to provide
enhancement for the images for better accoutrement, basic morphological algorithms will be used
and for pattern recognition, clustering algorithm is used and for determining shortest path,
Djikistra shortest path algorithm will be implemented.
2. HOW IS THE PROPOSED CONCEPT BETTER THAN BASE CONCEPT?
Base Paper: The base paper uses image processing technology to capture the images of the
ambulance that is approaching the signal. The one drawback that it had was the distance
constraint due to the use of RF transmitter and Receiver to generate RF signals in order to
enhance the performance of detection of the ambulance presence.
Proposed Concept: The proposed concept too uses image processing technology to capture
images. The difference is that here GPS system is used as a replacement for RF transmitter and
receiver module in every ambulances. The usage of GPS module overcomes the distance
constraint problem and also increases the accuracy of locating the ambulance to the near the
traffic signal. The nearest ambulance is located using Djikstra’s algorithm.
Also, the idea of using proximity sensors in the proposed concept improves the efficiency and
accuracy of tracking the ambulance presence amidst the traffic.
3. PROPOSED CONCEPT - HOW IT WORKS???
When the road is completely filled with traffic, it is necessary to have natural traffic signal
changes for ambulances that are in very critical situation to save human lives. Here the motion
camera that has been placed in traffic signals captures the 3-D Images of vehicles in roads to
automatically trigger the signal to green from the distance where the ambulance has been viewed.
In order to determine the closest proximity of the ambulance and from which end the ambulance
is approaching we have proximity sensor transmitter, that will be placed in ambulances and
3. International Journal of Computer Science & Information Technology (IJCSIT) Vol 5, No 4, August 2013
133
receivers that will be placed in all traffic signals, which calculates the distance and speed of the
ambulance to change the signal.
3.1. Motion Camera
The motion camera will be placed in the traffic signals which captures the 3D images in x,y,z
plane and determines the location of ambulance and thereby triggers the traffic signal. The
unique thing and main use of image capturing is that, all the ambulances will have name
AMBULANCE in reverse manner such as ‘ECNALUBMA’; this will be used as the primary
image recognition pattern.
The motion camera working on Integrated circuits is the major element used in the process of
detecting the presence of ambulances. These cameras mainly focus on the parameters like swing
angles, actual pan, zooming factor, tilt, and scaled focal length of the camera.
Figure 1: The camera coordinate system, image coordinate system and perspective imaging.
Let (X, Y, Z) be considered as a co-ordinate system of the camera. Here, the image plane will be
lying perpendicular to Z-axis along with its centre which is located at the point (0,0,f). Here,
based on perspective projection P=(X, Y, Z) and the 3D space is projected onto the point, where
p=(x,y) and the values of x and y be fX/z and fY/z receptively. We will be detracting some of the
motion parameters such as,
1. Pan angle a: rotation angle around the Y-axis
2. Zoom factors: ratio of the camera focal lengths between two image frames
3. Tilt angle/3 rotation angle around the X-axis
4. Translation vector t = (t „ ty, tz) T•
5. Swing angle ry: rotation angle around the Z-axis.
3.2. Smoothing Filter:
A smoothing filter is mainly used to replace the each pixel values that are present in input image
with its neighbouring images. This in turn, will eliminate the pixel values that are not relevant to
its surroundings. It will be like other kernel filters, which considers size and shape of its
neighbourhood to calculate sampling.
4. International Journal of Computer Science & Information Technology (IJCSIT) Vol 5, No 4, August 2013
134
The following image will demonstrate the difference between the normal image and smoothing
image. We will also be using the Gaussian filter for smoothing the image. Gaussian filter, a bell
shaped hump will screen the high spatial frequencies along with the noise and thereby produce
the smoothing effect. The distortion in signal will be reduced by smoothing filter, which mainly
focuses on the primary image eliminating the unnecessary surroundings.
Fig: a. before smoothing b. after smoothing
The Gaussian filter ID is given as,
2
2
2
2
1)(
x
exG
Where, σ is standard deviation of distribution in the Gaussian filter.
3.3. Sharpening filter:
The sharpening filter is used to adjust the contrast of the image and also to enhance the edges of
objects. Generally, the sharpening filters (High-pass filters) are allowed to pass and delete the
low-frequency components. Generally, these sharpening filters will eliminate the noise distortion
and provides the proper visibility and image quality, when it is being captured by the camera. The
sharpening filters are generally classified as,
1. Derivative filter
2. Laplace filter
3. High pass filter and
4. High boost filter.
Here, we are using the high boost filter to enhance the image further by using low pass.
High boost = A * original - low pass
= (A-1) * original + (original – low pass)
= (A-1) * original + high pass
5. International Journal of Computer Science & Information Technology (IJCSIT) Vol 5, No 4, August 2013
135
Fig a) before sharpening b) after sharpening
3.3. Avoid Image Blur during image capture
Three types of blur which usually occur in image processing are motion, Gaussian, and
compression blurs.
Motion blur maybe due to object movement when a camera shutter remains open for an extended
period of time and the object motion within this interval is visible in a single snapshot. It can also
be caused by camera movement.
Gaussian blur is made by a soft lens to spread out the light on the focal plane, rather than all
going toward a spot. It produces a smoothing effect by removing image details or noises.
[
Compression blur is triggered by the loss of high-frequency components in JPEG compression.
The following image describes the above types of image blurs available while capturing an
image.
6. International Journal of Computer Science & Information Technology (IJCSIT) Vol 5, No 4, August 2013
136
Fig: (a)Original image, (b)motion blur at orientation 45 degrees and magnitude 40, (c) Gaussian blur with a
17 x 17 window, (d) compression blur with compression ratio of 1:160.
Let f (xi) denotes the IQM score of an image under the degree of blur xi. The IQMs used for
measuring image blurs must satisfy the monotonically increasing or decreasing property.
(i.e.) if xi+1> xi, then f (xi+1)-f (xi) >0 for monotonically increasing (or) f (xi+1) - f (xi) < 0 for
monotonically decreasing property. The sensitivity of IQMs is defined as the score of the
aggregate relative distance:
i i
ii
xf
xfxf
)(
)()( 1
Nine IQMs, which are grouped into three categories based on pixel distance, correlation, and
mean square error, are explained as follows,
Let F (j,k) denote the pixel value of row j and column k in a reference image of size Mx N, and
F^ (j,k) denote the pixel value in a testing image.
7. International Journal of Computer Science & Information Technology (IJCSIT) Vol 5, No 4, August 2013
137
Category I: IQMs based on pixel distance
1. AD (average distance)
M
j
N
k
MNkjFkjFAD 1 1
/),(),(
2. L2D (L2 Euclidean distance)
2/1
1 1
2
),(),(
1
2
M
j
N
k
kjFkjF
MN
DL
Category II: IQMs based on correlation
3. SC (structure content)
M
j
N
k
M
j
N
k
kjFkjFSC 1 1
2
1 1
2
),(/),(
4. IF (image fidelity)
)),(/)),(),(((1 1 1
2
1 1
2
M
j
N
k
M
j
N
k
kjFkjFkjFIF
5. NK (N cross-correlation)
M
j
N
k
M
j
N
k
kjFkjFkjFNK 1 1 1 1
2
),(/),(),(
Category III: IQMs based on mean square error
6. NMSE (normal mean square error)
M
j
N
k
M
j
N
k
kjFkjFkjFNMSE 1 1 1 1
22
),(/)),(),((
7. LMSE (least mean square error)
M
j
N
k
M
j
N
k
kjFOkjFkjFLMSE 1 1 1 1
22
)),((/)),(),((
8. PMSE (peak mean square error)
2
1 1 ,
2
)]},([max/)],(),([
1
kjFkjFkjF
MN
PMSE
M
j
N
k kj
9. PSNR (peak signal to noise ratio)
2/1
1 1
2
10 })],(),([/{255{log20
M
j
N
k
kjFkjFPSNR
3.4. Pattern Recognition
In order to recognize the pattern of the ambulance in heavy traffic, we will be using the clustering
algorithm, in particular known as “two-pass mode clustering algorithm”. This algorithm requires
and processes only the registered multi-spectral image, twice. Here, the pattern of ambulance will
be imparted in the device and whenever the motion camera finds the pattern similar to that of
recognized pattern, it will be recognized. In clustering algorithm, there are two passes available.
In first pass, the mean vectors of all clusters will be generated and in the next pass, each every
8. International Journal of Computer Science & Information Technology (IJCSIT) Vol 5, No 4, August 2013
138
pixel will be assigned to a cluster that represents a single type, so as to determine the pattern
exactly.
The notations that will be used in this algorithm is given below:
B: It represents the total number of bands used. These numbers are the dimensionality in spectral
space. Here we are using 3D spectral space.
Cmax: It represents the maximum number of clusters
r (P,k): the distance between mean vector of current cluster (k) and gray value vector of pixel p.
It is given as
2/12
1
)))(((),( i
B
i i PkMeankPr
Where, 1 <= k<=Cmax, MEAN denoted the mean value of cluster k in band i, Pi denotes the gray
value in band I of pixel p.
R is the constant radius in spectral space used to decide the mean vector of new cluster. If the
value of R is lesser then r, then new cluster will be generated.
d(k1,k2) represents the difference between mean vector of two different clusters k1 and k2,
where 1<=k1,k2<=Cmax and k1 k2.
D is the constant radius in spectral space, which is used to determine whether two distinct clusters
k1 and k2 should be emerged or not.
N is the constant that represents the total number of pixels to be evaluated.
n (k) is the total number accumulated in cluster k.
Pass 1: Cluster's Mean vector establishment:
Here, the gray value vector of first pixel is placed as initial cluster's mean of cluster I. Then Mean
is calculated as
1)(
)()(
)(
kn
PknkMEAN
kMEAN ioldi
newi
If the above equation is used, then the values present in the equation ntotal (total number of
pixels) and n (k) will be incremented by one. This process will be repeated until the new image
has been placed. If the value of K or N is lesser than n total and is equal to Cmax, then the
process, which has been repeating will be terminated. The distance between the two mean vectors
will be used to calculate the recognition pattern. The decision radius finally is mainly dependent
upon the condition to activate the clusters and to merge it finally. If the value of d is lesser than or
equal to decision radius, then two clusters will be merged and also new mean vector will be
determined.
)()(
)()()()(
)(
21
2221
knkn
knkMEANknkMEAN
kMEAN ii
newi
9. International Journal of Computer Science & Information Technology (IJCSIT) Vol 5, No 4, August 2013
139
Where, 1<=k, k1, k2<= Cmax and also k1≠k2. Now, the total number of pixels in the new cluster
n (k) will be sum of the n (k1) and n (k2). At last, the number of clusters are built as the group of
individual pixels and its mean vectors will be determined in the second pass
Pass 2: Pixel Classification
Pass 2 in mainly used to classify each and every pixel into one of the clusters that has been built
in pass 1. The minimum distance method will be adopted here, where the clusters will recognize
the images that are present near and by using the minimum distance method, the pixels with
spectral features will be merged together, so as to ensure the efficient reliability of the merged
images. The pixels will be recognized by the motion camera that has been placed in traffic signals
and thereby, the images of ambulance will be clearly recognized by these pass 2 merged image,
with the image that has been present closer to the camera will be identified first.
3.5. Determine the nearest ambulance (Shortest path Algorithm)
Fig: Djikstra’s Algorithm – Determine the shortest path
The idea behind the shortest path algorithm (Dijkstra's algorithm) is to identify the nearest
ambulance in the traffic when there is a case of ambulances coming from more than one side.
Since roads come in varying lengths we want to work on weighted graphs for this problem. A
weighted graph is simply a graph where each edge e is assigned a non-negative value called the
weight, w (e), of the edge. A path is a sequence of vertices p = (v1,...,vn) such that vi ~ vi+1. Set ei
= (vi, vi+1). The length of a path p is d (p) = &Sigma w (ei). For convenience we will also write w
(u,v) to denote the weight of the edge (u,v). The idea behind Dijkstra's algorithm is breadth-first
search (BFS). This type of search explores vertices by spreading out as new vertices are found.
Fig: FPGA-based Dijkstra’s shortest pathalgorithm
10. International Journal of Computer Science & Information Technology (IJCSIT) Vol 5, No 4, August 2013
140
3.6. Why GPS - Global Positioning System replaces RF?
Global Positioning System tracking is a method of working out exactly where something is. It is a
worldwide radio-navigation system formed from the constellation of 24 satellites and their ground
stations. A GPS tracking system, for example, may be placed in a vehicle, on a cell phone, or on
special GPS devices, which can either be a fixed or portable unit. GPS works by providing
information on exact location. It can also track the movement of a vehicle or person. Because of
the above flexibility of accessing the modules anywhere across the globe, the biggest
disadvantage of distance constraint will be overcome over RF trans receiver modules.
3.7. How GPS is used here to track the ambulance?
Every ambulance is provided with a vehicle based tracking unit which will provide the details to
the traffic control station. The control station/remote access server location is equipped with a
Desktop Computer and a modem corresponding to the particular Radio used for communication
between Ambulance and the Control Station. Also, there is a GPS receiver which will keep track
of the ambulance position nearest to the signal. The output of the GPS receiver will be helpful in
triggering the signal green when the ambulance approaches the signal. Since some control
stations have direct control over the traffic signal, the geographical location of the ambulance is
also sent to the control station who can act accordingly when an ambulance is nearest to the signal
or in case of any emergency.
Fig: GPS vehicle tracking system involved in identifying the geographical coordinates of the ambulance.
A vehicle tracking system combines the installation of an electronic device in a vehicle, or fleet of
vehicles, with purpose-designed computer software at least at one operational base to enable the
owner or a third party to track the vehicle's location, collecting data in the process from the field
and deliver it to the base of operation. Modern vehicle tracking systems commonly use GPS
technology for locating the vehicle. Vehicle information can be viewed on electronic maps via the
Internet or specialized software. Urban public transit authorities/traffic control department
personnel are an increasingly common user of vehicle tracking systems, particularly in large
cities. So based on the location of the ambulance nearest to the signal, the traffic signal GPS
receiver module receives the input data from the transmitter and the signal for that direction is
changed to green to allow the ambulance comfortably and swiftly pass the signal.
3.8. GPS transmitter and Receiver circuits
The below image shows the simple GPS transmitter and receiver circuit which helps in
identifying the exact position of the vehicle (ambulance).
11. International Journal of Computer Science & Information Technology (IJCSIT) Vol 5, No 4, August 2013
141
Fig: GPS transmitter receiver circuit
3.8. Why Proximity sensors?
The idea of using proximity sensors in the proposed concept improves the efficiency and
accuracy of tracking the ambulance presence amidst the traffic. These sensors are sensitive to
small changes in the input and this helps in the calculative changing of signal immediately. Every
ambulance will be attached with a proximity sensor device which emit the signals in particular
frequencies to the proximity receiver that has been placed in traffic signals. The receiver that has
been placed in the traffic signals will receive the signals transmitted by ambulance based on the
approach speed of the ambulance. These signals will enable the receiver to identify the speed of
the ambulance, thereby estimating the distance of the ambulance from the traffic signal. The
output of the proximity sensor receiver module is available to processing unit to change the signal
to green accordingly.
4. IMPACT ON HUMAN LIVES
Current Scenario:
Now-a-days due to more luxurious living, more four wheelers have replaced 2-wheelers.
Moreover, industrialization (tech-parks) and need for space have caused more congestion. This in
turn increases traffic. Amidst all these frenzied life, one forgets the importance of human life.
After this work:
With the implementation of this idea, more lives can be saved. Due to the implementation of this
signal generator in every ambulance and image processing techniques, GPS modules, etc., the
ambulance would be able to reach the hospital on time which in turn would save a million lives.
5. FUTURE SCOPE
The current proposed concept of using GPS to replace the RF transmitter in order to overcome the
distance constraint can be extended to alert the nearest ambulance from the control area, to rush
the ambulance to the accident spot and provide the help to the injured person(s).
6. CONCLUSION
Thus the real time implementation of proposed concept of implementing GPS modules in
ambulances and image processing technology in traffic rich areas could ease the difficulties faced
during jams by ambulances when rushing to the hospital or to the injured spot.
12. International Journal of Computer Science & Information Technology (IJCSIT) Vol 5, No 4, August 2013
142
REFERENCES
[1] Manoj Prabahkar, Manoj Kumar & Dhilip Narayan (May 2013), “IMPACT OF IMAGE
PROCESSING IN SAVING THE HUMAN LIFE BY AUTOMATING TRAFFIC SIGNALS”
published in IJSRN, Volume 1 Issue 3.
[2] FRANK Y. SHIH, “IMAGE PROCESSING AND PATTERN RECOGNITION - Fundamentals and
Techniques” A JOHN WILEY & SONS, INC., Pubilication, Copyrights 2010
[3] STrobotix, Chandigarh labs and Chawla Radios, “RF based wireless remote”
[4] Yoshihiro Ikefuji, Sadakazu Murakami“Video Signal Generator circuit and video image processing
device using the same” , Patent Number – 5311296, Rohm Co., Ltd., May10, 1994
[5] Yap-Peng Tan, Sanjeev R. Kulkarni, Peter J. Ramadge, "A NEW METHOD FOR CAMERA
MOTION PARAMETER ESTIMATION"
[6] BRB900 GPS Telemetry System May 10, 2011, Version 0.05.
[7] http://eoinbailey.com/blog/dijkstras-algorithm-illustrated-explanation
[8 ]http://www.articlesbase.com/technology-articles/advantages-disadvantages-and-applications-of-
motion-capture-217465.html
[9] http://www.cs.princeton.edu/~rs/AlgsDS07/15ShortestPaths
[10] https://www.linxtechnologies.com/en/products/modules/lr-rf-transmitter-receiver
Authors
Manoj Prabhakar is a Systems Engineer in Tata Consultancy Services. He pursued the
Bachelor of Technology in Information Technology in Anna University in Chennai and
now pursuing Master of Business Administration in Anna University. His researches
have been mainly inclined towards the development of nation with some social factors
included in it. His other projects are also based on widely spread social issues and
suggesting a solution for it. He is also a part of Peace and Humanity organization to
support people. He has also worked in Marketing Research Management of
CITIBANK N.A
Manoj Kumar is a Systems Engineer in Tata Consultancy Services. He pursued the
Bachelor of Technology in Information Technology in Anna University in Chennai and
now pursuing Master of Business Administration in Anna University. He is currently
working Health Care Project of CITIBANK N.A