Nowadays, image processing has become one of the widely used computer aided science. Two major branches of this scientific field are image enhancement and machine vision. Machine vision has many applications and demands in robotic and defense industries. Detecting distance of objects is
one of the extensive research in the defense industry and robotic industries that a lot of annual projects have been involved in this issue both inside and outside the country. So, in this paper, an accurate algorithm is presented for measuring the distance of the objects from a camera. In this method, a laser
transmitter is used alongside a regular webcam. The laser light is transmitted to the desired object and then the distance of the object is calculated using image processing methods and mathematical and geometric relations. The performance of the proposed algorithm was evaluated using MATLAB software. The accuracy rate of distance detection is up to 99.62%. The results
also has shown that the presented algorithms make the obstacle distance measurement more reliable. Finally, the performance of the proposed algorithm was compared with other methods from different literatures.
Uncompressed Video Streaming in Wireless Channel without Interpolation using ...IJASRD Journal
Uncompressed video transmission recently paying attention because low end-to-end latency, good video quality and low convolution. In this method put forward a real-time uncompressed video diffusion system, where Unequal bit Allocation (UBA) approach are adopted to the end-to-end mean square error (MSE). Based on the Full search and logarithm search algorithm using the method. Video is improved largely and it provides that the different-level UBA scheme outperforms the conservative two-level of unequal bit allocation scheme in the stipulations of the average peak-signalto-noise (PSNR) at restrained SNRs, and the proposed adaptive UBA approach can good visual quality and the wireless communication.The pixel motion estimation is used correct the motion vector prediction in the H.264/AVC video coding. The proposed method solves the more complexity of the calculation of the fractional-pixel motion estimated video coding resolution is increased.
Implementation of Object Tracking for Real Time VideoIDES Editor
Real-time tracking of object boundaries is an
important task in many vision applications. Here we propose
an approach to implement the level set method. This approach
does not need to solve any partial differential equations (PDFs),
thus reducing the computation dramatically compared with
optimized narrow band techniques proposed before. With our
approach, real-time level-set based video tracking can be
achieved.
PC-based Vision System for Operating Parameter Identification on a CNC MachineIDES Editor
Identification of suitable or optimum operating
parameters on a CNC machine is a non-trivial task. Especially
when the material of the component changes, operating
parameters need to be suitably varied. In this paper, a PCbased
vision system is presented for the automatic identification
of component material and appropriate selection of operating
parameters. The objective of this work is to develop a support
system to aid the operator in quick identification of machining
parameters
Control of a Movable Robot Head Using Vision-Based Object TrackingIJECEIAES
This paper presents a visual tracking system to support the movement of the robot head for detecting the existence of objects. Object identification and object position estimation were conducted using image-based processing. The movement of the robot head was in four directions namely to the right, left, top, and bottom of the robot head. Based on the distance of the object, it shifted the object to many points to assess the accuracy of the process of tracking the object. The targeted objects are detected through several processes, namely normalization of RGB images, thresholding, and object marking. The process of tracking the object conducted by the robot head varied in 40 various object points with high accuracy. The further the object’s distance to the robot, the smaller the corner of the movement of the robot produced compared to the movement of the robot head to track an object that was closer even though with the same distance stimulant shift object. However, for the distance and the shift of the same object, the level of accuracy showed almost the same results. The results showed the movement of the robot head to track the object under the head of the robot produced the movement with a larger angular error compared to the movement of the robot head in another direction even though with the stimulant distance of the same object position and the distance shift of the same object.
Smqt Based Fingerprint Enhancement And Encryption For Border Crossing Securit...theijes
Biometric passport (e-passport) is to prevent the illegitimate entry of traveler into a particular country and border the use of counterfeit documents by more accurate identification of an individual. The electronic passport, as it is sometimes called, represents a bold proposal in the procedure of two new technologies: cryptography authentication protocols and biometrics (face, fingerprints, palm prints and iris).The goal of the adoption of the electronic passport is not only to accelerate processing at border crossings, but also to increase safety measures. Adaptive fingerprint enhancement method is used to enhance the fingerprint image. The term adaptive implies that parameters of the method are automatically adjusted based on the input fingerprint image. The adaptive fingerprint enhancement method comprises five processing blocks. 1) Pre-processing; 2) global analysis; 3) local analysis; and 4) matched filtering; 4) Image segmentation. In the pre-processing and local analysis blocks, a nonlinear dynamic range adjustment method, SMQT is used. These processing blocks yield an improved and new adaptive fingerprint image processing method. . For assuring security cryptography can be used with enhancement technique for encrypting the enhanced image so as to provide additional protection against fake. For this an image encryption approach using stream ciphers based on non linear filter generator along with AES encryption is used here. In this work a novel image encryption scheme using stream cipher algorithm based on nonlinear filter generator is considered. In this work a novel image encryption scheme is proposed based on stream cipher algorithm using pseudorandom generator with filtering function. This algorithm makes it possible to cipher and decipher images by guaranteeing a maximum security. The proposed cryptosystem is based on the use the linear feedback shift register (LFSR) with large secret key filtered by resilient function whose resiliency order, algebraic degree and nonlinearity attain Siegenthaler’s and Sarkar, al.’s bounds. This scheme is simple and highly efficient.
Abstract Edge detection is a fundamental tool used in most image processing applications. We proposed a simple, fast and efficient technique to detect the edge for the identifying, locating sharp discontinuities in an image and boundary of an image. In this paper, we found that proposed method called LookUp Table performs well, which requires least computational time as compared to conventional Edge Detection techniques. And also in this paper we presented a comparative performance of various conventional Edge Detection Techniques. Keywords: Edge detectors, Lookup table.
Currently, magnetic resonance imaging (MRI) has been utilized extensively to obtain high contrast medical image due to its safety which can be applied repetitively. To extract important information from an MRI medical images, an efficient image segmentation or edge detection is required. Edges are represented as important contour features in the medical image since they are the boundaries where distinct intensity changes or discontinuities occur. However, in practices, it is found rather difficult to design an edge detector that is capable of finding all the true edges in an image as there is always noise, and the subjectivity of sensitiveness in detecting the edges. Many traditional algorithms have been proposed to detect the edge, such as Canny, Sobel, Prewitt, Roberts, Zerocross, and Laplacian of Gaussian (LoG). Moreover, many researches have shown the potential of using Artificial Neural Network (ANN) for edge detection. Although many algorithms have been conducted on edge detection for medical images, however higher computational cost and subjective image quality could be further improved. Therefore, the objective of this paper is to develop a fast ANN based edge detection algorithm for MRI medical images. First, we developed features based on horizontal, vertical, and diagonal difference. Then, Canny edge detector will be used as the training output. Finally, optimized parameters will be obtained, including number of hidden layers and output threshold. The edge detection image will be analysed its quality subjectively and computational. Results showed that the proposed algorithm provided better image quality while it has faster processing time around three times time compared to other traditional algorithms, such as Sobel and Canny edge detector.
Uncompressed Video Streaming in Wireless Channel without Interpolation using ...IJASRD Journal
Uncompressed video transmission recently paying attention because low end-to-end latency, good video quality and low convolution. In this method put forward a real-time uncompressed video diffusion system, where Unequal bit Allocation (UBA) approach are adopted to the end-to-end mean square error (MSE). Based on the Full search and logarithm search algorithm using the method. Video is improved largely and it provides that the different-level UBA scheme outperforms the conservative two-level of unequal bit allocation scheme in the stipulations of the average peak-signalto-noise (PSNR) at restrained SNRs, and the proposed adaptive UBA approach can good visual quality and the wireless communication.The pixel motion estimation is used correct the motion vector prediction in the H.264/AVC video coding. The proposed method solves the more complexity of the calculation of the fractional-pixel motion estimated video coding resolution is increased.
Implementation of Object Tracking for Real Time VideoIDES Editor
Real-time tracking of object boundaries is an
important task in many vision applications. Here we propose
an approach to implement the level set method. This approach
does not need to solve any partial differential equations (PDFs),
thus reducing the computation dramatically compared with
optimized narrow band techniques proposed before. With our
approach, real-time level-set based video tracking can be
achieved.
PC-based Vision System for Operating Parameter Identification on a CNC MachineIDES Editor
Identification of suitable or optimum operating
parameters on a CNC machine is a non-trivial task. Especially
when the material of the component changes, operating
parameters need to be suitably varied. In this paper, a PCbased
vision system is presented for the automatic identification
of component material and appropriate selection of operating
parameters. The objective of this work is to develop a support
system to aid the operator in quick identification of machining
parameters
Control of a Movable Robot Head Using Vision-Based Object TrackingIJECEIAES
This paper presents a visual tracking system to support the movement of the robot head for detecting the existence of objects. Object identification and object position estimation were conducted using image-based processing. The movement of the robot head was in four directions namely to the right, left, top, and bottom of the robot head. Based on the distance of the object, it shifted the object to many points to assess the accuracy of the process of tracking the object. The targeted objects are detected through several processes, namely normalization of RGB images, thresholding, and object marking. The process of tracking the object conducted by the robot head varied in 40 various object points with high accuracy. The further the object’s distance to the robot, the smaller the corner of the movement of the robot produced compared to the movement of the robot head to track an object that was closer even though with the same distance stimulant shift object. However, for the distance and the shift of the same object, the level of accuracy showed almost the same results. The results showed the movement of the robot head to track the object under the head of the robot produced the movement with a larger angular error compared to the movement of the robot head in another direction even though with the stimulant distance of the same object position and the distance shift of the same object.
Smqt Based Fingerprint Enhancement And Encryption For Border Crossing Securit...theijes
Biometric passport (e-passport) is to prevent the illegitimate entry of traveler into a particular country and border the use of counterfeit documents by more accurate identification of an individual. The electronic passport, as it is sometimes called, represents a bold proposal in the procedure of two new technologies: cryptography authentication protocols and biometrics (face, fingerprints, palm prints and iris).The goal of the adoption of the electronic passport is not only to accelerate processing at border crossings, but also to increase safety measures. Adaptive fingerprint enhancement method is used to enhance the fingerprint image. The term adaptive implies that parameters of the method are automatically adjusted based on the input fingerprint image. The adaptive fingerprint enhancement method comprises five processing blocks. 1) Pre-processing; 2) global analysis; 3) local analysis; and 4) matched filtering; 4) Image segmentation. In the pre-processing and local analysis blocks, a nonlinear dynamic range adjustment method, SMQT is used. These processing blocks yield an improved and new adaptive fingerprint image processing method. . For assuring security cryptography can be used with enhancement technique for encrypting the enhanced image so as to provide additional protection against fake. For this an image encryption approach using stream ciphers based on non linear filter generator along with AES encryption is used here. In this work a novel image encryption scheme using stream cipher algorithm based on nonlinear filter generator is considered. In this work a novel image encryption scheme is proposed based on stream cipher algorithm using pseudorandom generator with filtering function. This algorithm makes it possible to cipher and decipher images by guaranteeing a maximum security. The proposed cryptosystem is based on the use the linear feedback shift register (LFSR) with large secret key filtered by resilient function whose resiliency order, algebraic degree and nonlinearity attain Siegenthaler’s and Sarkar, al.’s bounds. This scheme is simple and highly efficient.
Abstract Edge detection is a fundamental tool used in most image processing applications. We proposed a simple, fast and efficient technique to detect the edge for the identifying, locating sharp discontinuities in an image and boundary of an image. In this paper, we found that proposed method called LookUp Table performs well, which requires least computational time as compared to conventional Edge Detection techniques. And also in this paper we presented a comparative performance of various conventional Edge Detection Techniques. Keywords: Edge detectors, Lookup table.
Currently, magnetic resonance imaging (MRI) has been utilized extensively to obtain high contrast medical image due to its safety which can be applied repetitively. To extract important information from an MRI medical images, an efficient image segmentation or edge detection is required. Edges are represented as important contour features in the medical image since they are the boundaries where distinct intensity changes or discontinuities occur. However, in practices, it is found rather difficult to design an edge detector that is capable of finding all the true edges in an image as there is always noise, and the subjectivity of sensitiveness in detecting the edges. Many traditional algorithms have been proposed to detect the edge, such as Canny, Sobel, Prewitt, Roberts, Zerocross, and Laplacian of Gaussian (LoG). Moreover, many researches have shown the potential of using Artificial Neural Network (ANN) for edge detection. Although many algorithms have been conducted on edge detection for medical images, however higher computational cost and subjective image quality could be further improved. Therefore, the objective of this paper is to develop a fast ANN based edge detection algorithm for MRI medical images. First, we developed features based on horizontal, vertical, and diagonal difference. Then, Canny edge detector will be used as the training output. Finally, optimized parameters will be obtained, including number of hidden layers and output threshold. The edge detection image will be analysed its quality subjectively and computational. Results showed that the proposed algorithm provided better image quality while it has faster processing time around three times time compared to other traditional algorithms, such as Sobel and Canny edge detector.
ABSTRACT Feature extraction plays a vital role in the analysis and interpretation of remotely sensed data. The two important components of Feature extraction are Image enhancement and information extraction. Image enhancement techniques help in improving the visibility of any portion or feature of the image. Information extraction techniques help in obtaining the statistical information about any particular feature or portion of the image. This presented work focuses on the various feature extraction techniques and area of optical character recognition is a particularly important in Image processing. Keywords— Image character recognition, Methods for Feature Extraction, Basic Gabor Filter, IDA, and PCA.
Applying edge density based region growing with frame difference for detectin...eSAT Publishing House
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
IJERA (International journal of Engineering Research and Applications) is International online, ... peer reviewed journal. For more detail or submit your article, please visit www.ijera.com
Medical Image Fusion Using Discrete Wavelet TransformIJERA Editor
Medical image fusion is the process of registering and combining multiple images from single or multiple imaging modalities to improve the imaging quality and reduce randomness and redundancy in order to increase the clinical applicability of medical images for diagnosis and assessment of medical problems. Multimodal medical image fusion algorithms and devices have shown notable achievements in improving clinical accuracy of decisions based on medical images. The domain where image fusion is readily used nowadays is in medical diagnostics to fuse medical images such as CT (Computed Tomography), MRI (Magnetic Resonance Imaging) and MRA. This paper aims to present a new algorithm to improve the quality of multimodality medical image fusion using Discrete Wavelet Transform (DWT) approach. Discrete Wavelet transform has been implemented using different fusion techniques including pixel averaging, maximum minimum and minimum maximum methods for medical image fusion. Performance of fusion is calculated on the basis of PSNR, MSE and the total processing time and the results demonstrate the effectiveness of fusion scheme based on wavelet transform.
Interactive Full-Body Motion Capture Using Infrared Sensor Network ijcga
Traditional motion capture (mocap) has been well-studied in visual science for the last decades. However the field is mostly about capturing precise animation to be used in specific applications after intensive post processing such as studying biomechanics or rigging models in movies. These data sets 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 the 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 markerless or mechanical sensorless motion capture. Furthermore a wide array of low-cost device are released that are easy to use for less mission critical applications. This paper describes 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 emphasizes on the need of minimum calculation overhead for better real time performance
while being able to maintain good scalability.
AN OPTIMAL SOLUTION FOR IMAGE EDGE DETECTION PROBLEM USING SIMPLIFIED GABOR W...IJCSEIT Journal
Edge detection plays a vital role in computer vision and image processing. Edge of the image is one of the
most significant features which are mainly used for image analyzing process. An efficient algorithm for
extracting the edge features of images using simplified version of Gabor Wavelet is proposed in this paper.
Conventional Gabor Wavelet is widely used for edge detection applications. Due do the high computational
complexity of conventional Gabor Wavelet, this may not be used for real time application. Simplified Gabor
wavelet based approach is highly effective at detecting both the location and orientation of edges. The
results proved that the performance of proposed Simplified version of Gabor wavelet is superior to
conventional Gabor Wavelet, other edge detection algorithm and other wavelet based approach. The
performance of the proposed method is proved with the help of FOM, PSNR and Average run time.
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
This paper presents crack detection in concrete structure based on fuzzy logic. Safety inspection of concrete structures is very important since it is closely related with the structural health and reliability. Automated structural health monitoring system becomes necessity in recent years that encourages various researches to be going on in this area. Cheap availability of digital cameras makes research work in this field easier. This paper presents digital image processing and fuzzy logic based efficient crack detection technique in concrete structure. Here features from digital image of concrete structure are extracted by using morphological image processing technique and then extracted features are fed to fuzzy logic to accurately identify the crack.
Under the certain circumstances of the low and unacceptable accuracy on image recognition, the feature
extraction method for optical images based on the wavelet space feature spectrum entropy is recently
studied. With this method, the principle that the energy is constant before and after the wavelet
transformation is employed to construct the wavelet energy pattern matrices, and the feature spectrum
entropy of singular value is extracted as the image features by singular value decomposition of the matrix.
At the same time, BP neural network is also applied in image recognition. The experimental results show
that high image recognition accuracy can be acquired by using the feature extraction method for optical
images proposed in this paper, which proves the validity of the method.
Fingerprint Registration Using Zernike Moments : An Approach for a Supervised...CSCJournals
In this work, we deal with contactless fingerprint biometrics. More specifically, we are interested in solving the problem of registration by taking into consideration some constraints such as finger rotation and translation. In the proposed method, the registration requires: (1) a segmentation technique to extract streaks, (2) a skeletonization technique to extract the center line streaks and (3) and landmarks extraction technique. The correspondence between the sets of control points, is obtained by calculating the descriptor vector of Zernike moments on a window of size RxR centered at each point. Comparison of correlation coefficients between the descriptor vectors of Zernike moments helps define the corresponding points. The estimation of parameters of the existing deformation between images is performed using RANSAC algorithm (Random SAmple Consensus) that suppresses wrong matches. Finally, performance evaluation is achieved on a set of fingerprint images where promising results are reported.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Matching algorithm performance analysis for autocalibration method of stereo ...TELKOMNIKA JOURNAL
Stereo vision is one of the interesting research topics in the computer vision field. Two cameras are used to generate a disparity map, resulting in the depth estimation. Camera calibration is the most important step in stereo vision. The calibration step is used to generate an intrinsic parameter of each camera to get a better disparity map. In general, the calibration process is done manually by using a chessboard pattern, but this process is an exhausting task. Self-calibration is an important ability required to overcome this problem. Self-calibration required a robust and good matching algorithm to find the key feature between images as reference. The purpose of this paper is to analyze the performance of three matching algorithms for the autocalibration process. The matching algorithms used in this research are SIFT, SURF, and ORB. The result shows that SIFT performs better than other methods.
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.
Stereo matching based on absolute differences for multiple objects detectionTELKOMNIKA JOURNAL
This article presents a new algorithm for object detection using stereo camera system. The problem to get an accurate object detion using stereo camera is the imprecise of matching process between two scenes with the same viewpoint. Hence, this article aims to reduce the incorrect matching pixel with four stages. This new algorithm is the combination of continuous process of matching cost computation, aggregation, optimization and filtering. The first stage is matching cost computation to acquire preliminary result using an absolute differences method. Then the second stage known as aggregation step uses a guided filter with fixed window support size. After that, the optimization stage uses winner-takes-all (WTA) approach which selects the smallest matching differences value and normalized it to the disparity level. The last stage in the framework uses a bilateral filter. It is effectively further decrease the error on the disparity map which contains information of object detection and locations. The proposed work produces low errors (i.e., 12.11% and 14.01% nonocc and all errors) based on the KITTI dataset and capable to perform much better compared with before the proposed framework and competitive with some newly available methods.
ABSTRACT Feature extraction plays a vital role in the analysis and interpretation of remotely sensed data. The two important components of Feature extraction are Image enhancement and information extraction. Image enhancement techniques help in improving the visibility of any portion or feature of the image. Information extraction techniques help in obtaining the statistical information about any particular feature or portion of the image. This presented work focuses on the various feature extraction techniques and area of optical character recognition is a particularly important in Image processing. Keywords— Image character recognition, Methods for Feature Extraction, Basic Gabor Filter, IDA, and PCA.
Applying edge density based region growing with frame difference for detectin...eSAT Publishing House
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
IJERA (International journal of Engineering Research and Applications) is International online, ... peer reviewed journal. For more detail or submit your article, please visit www.ijera.com
Medical Image Fusion Using Discrete Wavelet TransformIJERA Editor
Medical image fusion is the process of registering and combining multiple images from single or multiple imaging modalities to improve the imaging quality and reduce randomness and redundancy in order to increase the clinical applicability of medical images for diagnosis and assessment of medical problems. Multimodal medical image fusion algorithms and devices have shown notable achievements in improving clinical accuracy of decisions based on medical images. The domain where image fusion is readily used nowadays is in medical diagnostics to fuse medical images such as CT (Computed Tomography), MRI (Magnetic Resonance Imaging) and MRA. This paper aims to present a new algorithm to improve the quality of multimodality medical image fusion using Discrete Wavelet Transform (DWT) approach. Discrete Wavelet transform has been implemented using different fusion techniques including pixel averaging, maximum minimum and minimum maximum methods for medical image fusion. Performance of fusion is calculated on the basis of PSNR, MSE and the total processing time and the results demonstrate the effectiveness of fusion scheme based on wavelet transform.
Interactive Full-Body Motion Capture Using Infrared Sensor Network ijcga
Traditional motion capture (mocap) has been well-studied in visual science for the last decades. However the field is mostly about capturing precise animation to be used in specific applications after intensive post processing such as studying biomechanics or rigging models in movies. These data sets 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 the 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 markerless or mechanical sensorless motion capture. Furthermore a wide array of low-cost device are released that are easy to use for less mission critical applications. This paper describes 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 emphasizes on the need of minimum calculation overhead for better real time performance
while being able to maintain good scalability.
AN OPTIMAL SOLUTION FOR IMAGE EDGE DETECTION PROBLEM USING SIMPLIFIED GABOR W...IJCSEIT Journal
Edge detection plays a vital role in computer vision and image processing. Edge of the image is one of the
most significant features which are mainly used for image analyzing process. An efficient algorithm for
extracting the edge features of images using simplified version of Gabor Wavelet is proposed in this paper.
Conventional Gabor Wavelet is widely used for edge detection applications. Due do the high computational
complexity of conventional Gabor Wavelet, this may not be used for real time application. Simplified Gabor
wavelet based approach is highly effective at detecting both the location and orientation of edges. The
results proved that the performance of proposed Simplified version of Gabor wavelet is superior to
conventional Gabor Wavelet, other edge detection algorithm and other wavelet based approach. The
performance of the proposed method is proved with the help of FOM, PSNR and Average run time.
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
This paper presents crack detection in concrete structure based on fuzzy logic. Safety inspection of concrete structures is very important since it is closely related with the structural health and reliability. Automated structural health monitoring system becomes necessity in recent years that encourages various researches to be going on in this area. Cheap availability of digital cameras makes research work in this field easier. This paper presents digital image processing and fuzzy logic based efficient crack detection technique in concrete structure. Here features from digital image of concrete structure are extracted by using morphological image processing technique and then extracted features are fed to fuzzy logic to accurately identify the crack.
Under the certain circumstances of the low and unacceptable accuracy on image recognition, the feature
extraction method for optical images based on the wavelet space feature spectrum entropy is recently
studied. With this method, the principle that the energy is constant before and after the wavelet
transformation is employed to construct the wavelet energy pattern matrices, and the feature spectrum
entropy of singular value is extracted as the image features by singular value decomposition of the matrix.
At the same time, BP neural network is also applied in image recognition. The experimental results show
that high image recognition accuracy can be acquired by using the feature extraction method for optical
images proposed in this paper, which proves the validity of the method.
Fingerprint Registration Using Zernike Moments : An Approach for a Supervised...CSCJournals
In this work, we deal with contactless fingerprint biometrics. More specifically, we are interested in solving the problem of registration by taking into consideration some constraints such as finger rotation and translation. In the proposed method, the registration requires: (1) a segmentation technique to extract streaks, (2) a skeletonization technique to extract the center line streaks and (3) and landmarks extraction technique. The correspondence between the sets of control points, is obtained by calculating the descriptor vector of Zernike moments on a window of size RxR centered at each point. Comparison of correlation coefficients between the descriptor vectors of Zernike moments helps define the corresponding points. The estimation of parameters of the existing deformation between images is performed using RANSAC algorithm (Random SAmple Consensus) that suppresses wrong matches. Finally, performance evaluation is achieved on a set of fingerprint images where promising results are reported.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Matching algorithm performance analysis for autocalibration method of stereo ...TELKOMNIKA JOURNAL
Stereo vision is one of the interesting research topics in the computer vision field. Two cameras are used to generate a disparity map, resulting in the depth estimation. Camera calibration is the most important step in stereo vision. The calibration step is used to generate an intrinsic parameter of each camera to get a better disparity map. In general, the calibration process is done manually by using a chessboard pattern, but this process is an exhausting task. Self-calibration is an important ability required to overcome this problem. Self-calibration required a robust and good matching algorithm to find the key feature between images as reference. The purpose of this paper is to analyze the performance of three matching algorithms for the autocalibration process. The matching algorithms used in this research are SIFT, SURF, and ORB. The result shows that SIFT performs better than other methods.
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.
Stereo matching based on absolute differences for multiple objects detectionTELKOMNIKA JOURNAL
This article presents a new algorithm for object detection using stereo camera system. The problem to get an accurate object detion using stereo camera is the imprecise of matching process between two scenes with the same viewpoint. Hence, this article aims to reduce the incorrect matching pixel with four stages. This new algorithm is the combination of continuous process of matching cost computation, aggregation, optimization and filtering. The first stage is matching cost computation to acquire preliminary result using an absolute differences method. Then the second stage known as aggregation step uses a guided filter with fixed window support size. After that, the optimization stage uses winner-takes-all (WTA) approach which selects the smallest matching differences value and normalized it to the disparity level. The last stage in the framework uses a bilateral filter. It is effectively further decrease the error on the disparity map which contains information of object detection and locations. The proposed work produces low errors (i.e., 12.11% and 14.01% nonocc and all errors) based on the KITTI dataset and capable to perform much better compared with before the proposed framework and competitive with some newly available methods.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Robotic navigation algorithm with machine vision IJECEIAES
In the field of robotics, it is essential to know the work area in which the agent is going to develop, for that reason, different methods of mapping and spatial location have been developed for different applications. In this article, a machine vision algorithm is proposed, which is responsible for identifying objects of interest within a work area and determining the polar coordinates to which they are related to the observer, applicable either with a fixed camera or in a mobile agent such as the one presented in this document. The developed algorithm was evaluated in two situations, determining the position of six objects in total around the mobile agent. These results were compared with the real position of each of the objects, reaching a high level of accuracy with an average error of 1.3271% in the distance and 2.8998% in the angle.
Goal location prediction based on deep learning using RGB-D camerajournalBEEI
In the navigation system, the desired destination position plays an essential role since the path planning algorithms takes a current location and goal location as inputs as well as the map of the surrounding environment. The generated path from path planning algorithm is used to guide a user to his final destination. This paper presents a proposed algorithm based on RGB-D camera to predict the goal coordinates in 2D occupancy grid map for visually impaired people navigation system. In recent years, deep learning methods have been used in many object detection tasks. So, the object detection method based on convolution neural network method is adopted in the proposed algorithm. The measuring distance between the current position of a sensor and the detected object depends on the depth data that is acquired from RGB-D camera. Both of the object detected coordinates and depth data has been integrated to get an accurate goal location in a 2D map. This proposed algorithm has been tested on various real-time scenarios. The experiments results indicate to the effectiveness of the proposed algorithm.
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.
REGISTRATION TECHNOLOGIES and THEIR CLASSIFICATION IN AUGMENTED REALITY THE K...IJCSEA Journal
The registration in augmented reality is process which merges virtual objects generated by computer with
real world image caught by camera. This paper describes the knowledge-based registration, computer
vision-based registration and tracker-based registration technology. This paper mainly focused on trackerbased registration technology in augmented reality. Also described method in tracker- based technology,
problem and solution.
REGISTRATION TECHNOLOGIES and THEIR CLASSIFICATION IN AUGMENTED REALITY THE K...IJCSEA Journal
The registration in augmented reality is process which merges virtual objects generated by computer with real world image caught by camera. This paper describes the knowledge-based registration, computer vision-based registration and tracker-based registration technology. This paper mainly focused on trackerbased
registration technology in augmented reality. Also described method in tracker- based technology, problem and solution.
Pose estimation algorithm for mobile augmented reality based on inertial sen...IJECEIAES
Augmented reality (AR) applications have become increasingly ubiquitous as it integrates virtual information such as images, 3D objects, video, and more to the real world, which further enhances the real environment. Many researchers have investigated the augmentation of the 3D object on the digital screen. However, certain loopholes exist in the existing system while estimating the object’s pose, making it inaccurate for mobile augmented reality (MAR) applications. Objects augmented in the current system have much jitter due to frame illumination changes, affecting the accuracy of vision-based pose estimation. This paper proposes to estimate the pose of an object by blending both vision-based techniques and micro electrical mechanical system (MEMS) sensor (gyroscope) to minimize the jitter problem in MAR. The algorithm used for feature detection and description is oriented FAST rotated BRIEF (ORB), whereas to evaluate the homography for pose estimation, random sample consensus (RANSAC) is used. Furthermore, gyroscope sensor data is incorporated with the vision-based pose estimation. We evaluated the performance of augmenting the 3D object using the techniques, vision-based, and incorporating the sensor data using the video data. After extensive experiments, the validity of the proposed method was superior to the existing vision-based pose estimation algorithms.
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.
Similar to An Accurate Scheme for Distance Measurement using an Ordinary Webcam (20)
Improving the Proactive Routing Protocol using Depth First Iterative Deepenin...Yayah Zakaria
Owing to the wireless and mobility nature, nodes in a mobile ad hoc network are not within the transmission range. It needs to transfer data through the multi-intermediate nodes. Opportunistic data forwarding is an assuring solution to make use of the broadcast environment of wireless communication links. Due to absence of source routing capability with efficient proactive routing protocol, it is not widely used. To rectify the
problem, we proposed memory and routing efficient proactive routing protocol using Depth-First Iterative-Deepening and hello messaging scheme. This protocol can conserve the topology information in every node in the network. In experimental analysis and discussion, we implemented the proposed work using NS2 simulator tool and proved that the proposed technique is performed well in terms of average delay, buffer and throughput.
Improvement at Network Planning using Heuristic Algorithm to Minimize Cost of...Yayah Zakaria
Wireless Mesh Networks (WMN) consists of wireless stations that are connected with each other in a semi-static configuration. Depending on the configuration of a WMN, different paths between nodes offer different levels of efficiency. One areas of research with regard to WMN is cost minimization. A Modified Binary Particle Swarm Optimization (MBPSO) approach was used to optimize cost. However, minimized cost does not
guarantee network performance. This paper thus, modified the minimization function to take into consideration the distance between the different nodes so as to enable better performance while maintaining cost balance. The results were positive with the PDR showing an approximate increase of 17.83% whereas the E2E delay saw an approximate decrease of 8.33%.
A Vertical Handover Algorithm in Integrated Macrocell Femtocell Networks Yayah Zakaria
The explosion in wireless telecommunication technologies has lead to a huge increase in the number of mobile users. The greater dependency on the mobile devices has raised the user’s expectations to always remain best connected. In the process, the user is always desiringgood signal strength even at certain black spots and indoors. Moreover, the exponential growth of
the number of mobile devices has overloaded macrocells. Femtocells have emerged out as a good promising solution for complete coverage indoors and for offloading macrocell. Therefore, a new handover strategy between femtocells and macrocell is proposed in this paper. The proposed handover
algorithm is mainly based on calculating equivalent received signal strength along with dynamic margin for performing handover. The simulation results of proposed algorithm are compared with the traditional algorithm. The proposed strategy shows improvement in two major performance parameters
namely reduction in unnecessary handovers and Packet Loss Ratio. The quantitative analysis further shows 55.27% and 23.03% reduction in packet loss ratio and 61.85% and 36.78% reduction in unnecessary handovers at a speed of 120kmph and 30kmph respectively. Moreover, the proposed algorithm proves to be an efficient solution for both slow and fast moving vehicles.
Symmetric Key based Encryption and Decryption using Lissajous Curve EquationsYayah Zakaria
Sender and receiver both uses two large similar prime numbers and uses parametric equations for swapping values of kx and by product of kx and ky is the common secret key. Generated secret key is used for encryption and decryption using ASCII key matrix of order 16X16. Applying playfair rules for encryption and decryption. Playfair is a digraph substitution cipher. Playfair makes use of pairs of letters for encryption and decryption. This
application makes use of all ASCII characters which makes brute force attack impossible.
Gain Flatness and Noise Figure Optimization of C-Band EDFA in 16-channels WDM...Yayah Zakaria
In this paper, Gain Flatness and Noise Figure of Erbium Doped Fiber Amplifier (EDFA) have been investigated in 16-channels Wavelength Division Multiplexing (WDM). Fiber Bragg Grating (FBG) is used in C-band with the aim to achieve flat EDFA output gain. The proposed model has been studied in detail to evaluate and to enhance the performance of the transmission system in terms of gain, noise figure and eye diagram of the
received signals. To that end, various design parameters have been investigated and optimized, such as frequency spacing, EDF length and temperature. To enhance the transmission system performance in terms of gain flatness, the Gain Flattening Filter (GFF) has been introduced in the design. To prove the efficiency of the new design, the optical transmission
system with optimized design parameters has been compared with a previous works in the literature. The simulation results show satisfactory performance with quasi-equalized gain for each channel of the WDM transmission system.
In this paper partial H-plane band-pass waveguide filter, utilizing a novel resonant structure comprising a metal window along with metal posts has been proposed to compactthe filter size. The metal windows and postshave been implemented transversely in a partial H-plane waveguides, which have
one-quarter cross section size compared to the conventional waveguides in the same frequency range. Partial H-plane band-pass waveguide filter with novel proposed resonant structures has considerably shorter longitudinal length compared to the conventional partial H-plane filters, so that they reduce both cross section size and the total length of the filter compared to
conventional H-plane filters, in the same frequency range. In the presented design procedure, the size and shape of each metal window and metal posts has been determined by fitting the transfer function of the proposed resonant structure to that of a desiredone, which is obtained from a suitable equivalent
circuit model. The design process is based on optimization using
electromagnetic simulator software, HFSS. A proposed partial H-plane bandpass
filter has been designed and simulated to verify usefulness and
performanceof the design method.
Vehicular Ad Hoc Networks: Growth and Survey for Three Layers Yayah Zakaria
A vehicular ad hoc network (VANET) is a mobile ad hoc network that allows wireless communication between vehicles, as well as between vehicles and roadside equipment. Communication between vehicles promotes safety and reliability, and can be a source of entertainment. We investigated the historical development, characteristics, and application fields of VANET and briefly introduced them in this study. Advantages and disadvantages were discussed based on our analysis and comparison of various classes of MAC and routing protocols applied to VANET. Ideas and breakthrough directions for inter-vehicle communication designs were proposed based on the
characteristics of VANET. This article also illustrates physical, MAC, and network layer in details which represent the three layers of VANET. The main works of the active research institute on VANET were introduced to help researchers track related advanced research achievements on the subject.
Barriers and Challenges to Telecardiology Adoption in Malaysia Context Yayah Zakaria
Mainly in infrastructure deficient communities, telecardiology is considered as a complement to insufficient cardiac care. Telecardiology can reduce travelling and waiting time, enables information sharing in shorter time and facilitate care in rural and remote areas. A qualitative study examined the perspectives of health care providers: cardiologist and general physician and
health care service receivers: patient and public towards telecardiology adoption. The barriers in telecardiology adoption were identified in this paper. It includes practicality of telecardiology, the need of education for staffs and administrators, ease of use, preferred face-to-face consultation,
cost and confidentiality. Improvements can be done by the implementers based on this study in order to promote telecardiology successfully in Malaysia.
Novel High-Gain Narrowband Waveguide-Fed Filtenna using Genetic Algorithm Yayah Zakaria
Filtenna is an antenna with filtering feature. There are many ways to design a filtenna. In this paper, a high-gain narrowband waveguide-fed aperture filtenna has been proposed and designed. A patterned plane, which is designed using genetic algorithm has been used at the open end of the waveguide fed, mounted on a conducting ground plane. To design the patterned pattern, magnetic field integral equation of the structure has been derived, so it has been solved using method of moments. The proposed filtenna has been simulated with HFSS that confirms the results obtained by method of moments. Finally, an unprinted dielectric as a superstrate has been used to enhance the gain of the filtenna. The filtenna bandwidth is 1.76% (160 MHz) which has the gain of 15.91 dB at the central frequency
of 9.45 GHz.
Improved Algorithm for Pathological and Normal Voices Identification Yayah Zakaria
There are a lot of papers on automatic classification between normal and pathological voices, but they have the lack in the degree of severity estimation of the identified voice disorders. Building a model of pathological and normal voices identification, that can also evaluate the degree of severity
of the identified voice disorders among students. In the present work, we present an automatic classifier using acoustical measurements on registered sustained vowels /a/ and pattern recognition tools based on neural networks. The training set was done by classifying students’ recorded voices based on threshold from the literature. We retrieve the pitch, jitter, shimmer and harmonic-to-noise ratio values of the speech utterance /a/, which constitute the input vector of the neural network. The degree of severity is estimated to evaluate how the parameters are far from the standard values based on the percent of normal and pathological values. In this work, the base data used for testing the proposed algorithm of the neural network is formed by healthy
and pathological voices from German database of voice disorders. The
performance of the proposed algorithm is evaluated in a term of the accuracy
(97.9%), sensitivity (1.6%), and specificity (95.1%). The classification rate is
90% for normal class and 95% for pathological class.
Uncertain Systems Order Reduction by Aggregation Method Yayah Zakaria
In the field of control engineering, approximating the higher-order system with its reduced model copes with more intricateproblems. These complex problems are addressed due to the usage of computing technologies and advanced algorithms. Reduction techniques enable the system from higherorder to lower-order form retaining the properties of former even after reduction. This document renders a method for demotion of uncertain systems based on State Space Analysis. Numerical examples are illustrated to show the accuracy of the proposed method.
A Three-Point Directional Search Block Matching Algorithm Yayah Zakaria
This paper proposes compact directional asymmetric search patterns, which we have named as three-point directional search (TDS). In most fast search motion estimation algorithms, a symmetric search pattern is usually set at the minimum block distortion point at each step of the search. The design of the
symmetrical pattern in these algorithms relies primarily on the assumption that the direction of convergence is equally alike in each direction with respect to the search center. Therefore, the monotonic property of real -world video sequences is not properly used by these algorithms. The strategy of TDS is to keep searching for the minimum block distortion point in the most probable directions, unlike the previous fast search motion estimation algorithms where all the directions are checked. Therefore, the proposed method significantly reduces the number of search points for locating a motion vector. Compared to conventional fast algorithms, the proposed method has the fastest search speed and most satisfactory PSNR values for
all test sequences.
Human Data Acquisition through Biometrics using LabVIEW Yayah Zakaria
Human Data Acquisition is an innovative work done based on fingerprints of a particular person. Using the fingerprints we can get each and every detail of any individual. Through this, the data acquired can be used in many applications such as Airport Security System, Voting System, and Employee login System, in finding the thieves etc. We in our project have implemented
in Voting System. In this we use the components such as MyDAQ which is data acquisition device. The coding here is in done in a Graphical Programming language named LabVIEW where the execution of any program is done in a sequential way or step by step according to the data received.
A Survey on Block Matching Algorithms for Video Coding Yayah Zakaria
Block matching algorithm (BMA) for motion estimation (ME) is the heart to many motion-compensated video-coding techniques/standards, such as ISO MPEG-1/2/4 and ITU-T H.261/262/263/264/265, to reduce the temporal redundancy between different frames. During the last three decades,
hundreds of fast block matching algorithms have been proposed. The shape and size of search patterns in motion estimation will influence more on the searching speed and quality of performance. This article provides an overview of the famous block matching algorithms and compares their computational complexity and motion prediction quality.
Identity Analysis of Egg Based on Digital and Thermal Imaging: Image Processi...Yayah Zakaria
This research was conducted to analyze the identification of eggs. The research processes use two tools, namely thermal imaging camera and smartphone camera. The identification process was done by using Matlab prototype tools. The image has been acquired by means of proficiency level, then analyzed and applied several methods. Image acquisition results of thermal imaging camera are processed using morphological dilation and do the complement in black and white (BW). While the digital image uses the merger method of morphological dilation and opening, and it doesn't need to be complemented. Labeling process is done, and the process of determining centroid and bounding box. The process has been done and it can be applied for identifying of chicken eggs with the accuracy rate of 100%. There are different methods of both images is obtained area (pixels) which is equivalent to the difference is very small as 6 x 10-3.
.
Recognition of Tomato Late Blight by using DWT and Component Analysis Yayah Zakaria
Plant disease recognition concept is one of the successful and important applications of image processing and able to provide accurate and useful information to timely prediction and control of plant diseases. In the study, the wavelet based features computed from RGB images of late blight infected images and healthy images. The extracted features submitted to Principal Component Analysis (PCA), Kernel Principal Component Analysis (KPCA) and Independent Component Analysis performed (ICA) for reducing dimensions in feature data processing and classification. To recognize and classify late blight from healthy plant images are classified into two classes i.e. late blight infected or healthy. The Euclidean Distance measure is used to compute the distance by these two classes of training and testing dataset for tomato late blight recognition and classification. Finally, the three-component analysis is compared for late blight recognition accuracy. The Kernel Principal Component Analysis (KPCA) yielded overall recognition accuracy with 96.4%.
Fuel Cell Impedance Model Parameters Optimization using a Genetic Algorithm Yayah Zakaria
The objective of this paper is the PEM fuel cell impedance model parameters identification. This work is a part of a larger work which is the diagnosis of the fuel cell which deals with the optimization and the parameters identification of the impedance complex model of the Nexa Ballard 1200 PEM fuel cell. The method used for the identification is a sample genetic algorithm and the proposed impedance model is based on electric parameters, which will be found from a sweeping of well determined frequency bands. In fact, the frequency spectrum is divided into bands according to the behavior of the fuel cell. So, this work is considered a first in the field of impedance spectroscopy So, this work is considered a first in the field of impedance spectroscopy. Indeed, the identification using genetic algorithm requires experimental measures of the fuel cell impedance to optimize and identify the impedance model parameters values. This method is characterized by a good precision compared to the numeric methods. The obtained results prove the effectiveness of this approach.
Noise Characterization in InAlAs/InGaAs/InP pHEMTs for Low Noise Applications Yayah Zakaria
In this paper, a noise revision of an InAlAs/InGaAs/InP psoeudomorphic high electron mobility transistor (pHEMT) in presented. The noise performances of the device were predicted over a range of frequencies from 1GHz to 100GHz. The minimum noise figure (NFmin), the noise resistance (Rn) and optimum source impedance (Zopt) were extracted using two
approaches. A physical model that includes diffusion noise and G-R noise models and an analytical model based on an improved PRC noise model that considers the feedback capacitance Cgd. The two approaches presented matched results allowing a good prediction of the noise behaviour. The
pHEMT was used to design a single stage S-band low noise amplifier (LNA). The LNA demonstrated a gain of 12.6dB with a return loss coefficient of 2.6dB at the input and greater than -7dB in the output and an overall noise figure less than 1dB.
Effect of Mobility on (I-V) Characteristics of Gaas MESFET Yayah Zakaria
We present in this paper an analytical model of the current–voltage (I-V) characteristics for submicron GaAs MESFET transistors. This model takes into account the analysis of the charge distribution in the active region and incorporate a field depended electron mobility, velocity saturation and charge
build-up in the channel. We propose in this frame work an algorithm of simulation based on mathematical expressions obtained previously. We propose a new mobility model describing the electric field-dependent. predictions of the simulator are compared with the experimental data [1] and
have been shown to be good.
Performance Analysis of Post Compensated Long Haul High Speed Coherent Optica...Yayah Zakaria
This paper addresses the performance analysis of OFDM transmission system based on coherent detection over high speed long haul optical links with high spectral efficiency modulation formats such as Quadrature Amplitude Modulation (QAM) as a mapping method prior to the OFDM multicarrier representation. Post compensation is used to compensate for
phase noise effects. Coherent detection for signal transmitted at bit rate of 40 Gbps is successfully achieved up to distance of 3200km. Performance is analyzed in terms of Symbol Error Rate and Error Vector Magnitude by varying Optical Signal to Noise Ratio (OSNR) and varying the length of the fiber i.e transmission distance. Transmission performance is also observed through constellation diagrams at different transmission distances and
different OSNRs.
Overview of the fundamental roles in Hydropower generation and the components involved in wider Electrical Engineering.
This paper presents the design and construction of hydroelectric dams from the hydrologist’s survey of the valley before construction, all aspects and involved disciplines, fluid dynamics, structural engineering, generation and mains frequency regulation to the very transmission of power through the network in the United Kingdom.
Author: Robbie Edward Sayers
Collaborators and co editors: Charlie Sims and Connor Healey.
(C) 2024 Robbie E. Sayers
Cosmetic shop management system project report.pdfKamal Acharya
Buying new cosmetic products is difficult. It can even be scary for those who have sensitive skin and are prone to skin trouble. The information needed to alleviate this problem is on the back of each product, but it's thought to interpret those ingredient lists unless you have a background in chemistry.
Instead of buying and hoping for the best, we can use data science to help us predict which products may be good fits for us. It includes various function programs to do the above mentioned tasks.
Data file handling has been effectively used in the program.
The automated cosmetic shop management system should deal with the automation of general workflow and administration process of the shop. The main processes of the system focus on customer's request where the system is able to search the most appropriate products and deliver it to the customers. It should help the employees to quickly identify the list of cosmetic product that have reached the minimum quantity and also keep a track of expired date for each cosmetic product. It should help the employees to find the rack number in which the product is placed.It is also Faster and more efficient way.
Hierarchical Digital Twin of a Naval Power SystemKerry Sado
A hierarchical digital twin of a Naval DC power system has been developed and experimentally verified. Similar to other state-of-the-art digital twins, this technology creates a digital replica of the physical system executed in real-time or faster, which can modify hardware controls. However, its advantage stems from distributing computational efforts by utilizing a hierarchical structure composed of lower-level digital twin blocks and a higher-level system digital twin. Each digital twin block is associated with a physical subsystem of the hardware and communicates with a singular system digital twin, which creates a system-level response. By extracting information from each level of the hierarchy, power system controls of the hardware were reconfigured autonomously. This hierarchical digital twin development offers several advantages over other digital twins, particularly in the field of naval power systems. The hierarchical structure allows for greater computational efficiency and scalability while the ability to autonomously reconfigure hardware controls offers increased flexibility and responsiveness. The hierarchical decomposition and models utilized were well aligned with the physical twin, as indicated by the maximum deviations between the developed digital twin hierarchy and the hardware.
Sachpazis:Terzaghi Bearing Capacity Estimation in simple terms with Calculati...Dr.Costas Sachpazis
Terzaghi's soil bearing capacity theory, developed by Karl Terzaghi, is a fundamental principle in geotechnical engineering used to determine the bearing capacity of shallow foundations. This theory provides a method to calculate the ultimate bearing capacity of soil, which is the maximum load per unit area that the soil can support without undergoing shear failure. The Calculation HTML Code included.
Immunizing Image Classifiers Against Localized Adversary Attacksgerogepatton
This paper addresses the vulnerability of deep learning models, particularly convolutional neural networks
(CNN)s, to adversarial attacks and presents a proactive training technique designed to counter them. We
introduce a novel volumization algorithm, which transforms 2D images into 3D volumetric representations.
When combined with 3D convolution and deep curriculum learning optimization (CLO), itsignificantly improves
the immunity of models against localized universal attacks by up to 40%. We evaluate our proposed approach
using contemporary CNN architectures and the modified Canadian Institute for Advanced Research (CIFAR-10
and CIFAR-100) and ImageNet Large Scale Visual Recognition Challenge (ILSVRC12) datasets, showcasing
accuracy improvements over previous techniques. The results indicate that the combination of the volumetric
input and curriculum learning holds significant promise for mitigating adversarial attacks without necessitating
adversary training.
Hybrid optimization of pumped hydro system and solar- Engr. Abdul-Azeez.pdffxintegritypublishin
Advancements in technology unveil a myriad of electrical and electronic breakthroughs geared towards efficiently harnessing limited resources to meet human energy demands. The optimization of hybrid solar PV panels and pumped hydro energy supply systems plays a pivotal role in utilizing natural resources effectively. This initiative not only benefits humanity but also fosters environmental sustainability. The study investigated the design optimization of these hybrid systems, focusing on understanding solar radiation patterns, identifying geographical influences on solar radiation, formulating a mathematical model for system optimization, and determining the optimal configuration of PV panels and pumped hydro storage. Through a comparative analysis approach and eight weeks of data collection, the study addressed key research questions related to solar radiation patterns and optimal system design. The findings highlighted regions with heightened solar radiation levels, showcasing substantial potential for power generation and emphasizing the system's efficiency. Optimizing system design significantly boosted power generation, promoted renewable energy utilization, and enhanced energy storage capacity. The study underscored the benefits of optimizing hybrid solar PV panels and pumped hydro energy supply systems for sustainable energy usage. Optimizing the design of solar PV panels and pumped hydro energy supply systems as examined across diverse climatic conditions in a developing country, not only enhances power generation but also improves the integration of renewable energy sources and boosts energy storage capacities, particularly beneficial for less economically prosperous regions. Additionally, the study provides valuable insights for advancing energy research in economically viable areas. Recommendations included conducting site-specific assessments, utilizing advanced modeling tools, implementing regular maintenance protocols, and enhancing communication among system components.
2. ISSN: 2088-8708
IJECE Vol. 7, No. 1, February 2017 : 209 – 215
210
measuring system based on eye-distance. The distance between centers of two eyes is used for measuring the
person to camera distance [5]. Mohammad used the infrared (IR) together with ultrasonic (US) sensors to
improve the overall vision systems of mobile robots [6]. Xiaoming et al. proposed a real-time method which
can measure distance using a modified camera. This method can only be performed within 3.21ms to achieve
acceptable accuracy [7]. Shrivastava et al. presented a distance measurement of an obstacle using separate
ultrasonic transmitter, receiver and a P89C51RD2 microcontroller [8]. Jinjin et al. introduced a single bit
cross correlation method to improve the range resolution of the ultrasonic distance measurement [9].
In this paper, we are looking for more advanced features and optimized basic design to achieve the
eligible design criteria. Nowadays, advanced portable cameras are widely used for the development of
assistive technologies based on image processing to achieve systems with high computational performance.
The main objective of this study is to present and evaluate the performance of the image processing
algorithm using a CMOS camera and a laser transmitter to measure the obstacle distance. If the desired
performance is achieved, this technique could be used for robot and machine vision applications and also, for
a variety of applications that require a virtual smart vision. For this reason, in this work we have tried to
approach progress comparison with other studies on the robots vision. In most of these studies, ultrasound
sensors are used to measure distance.
The rest of the paper is organized as follows. Section 2 describes our experimental setup for image
acquisition and also related problems and their solutions. Section 3 gives simulation and experimental results.
Section 4 draws conclusions.
2. METHODOLOGY
There are various methods to measure the distance of objects using camera. In this work, a laser
transmitter alongside a camera have been used. Laser transmitter and camera have been located in a same
horizontal direction. Laser light is emitted to the desired object. Due to the distance of the desired object from
camera, the horizontal location of the laser light in the image is different. Thus, the distance to the subject can
be easily calculated by laser light processing and extraction of its horizontal location in the image and using a
simple mathematical model based on the displacement of the laser light.
2.1. Algorithm Design Process
The design process is illustrated in Figure 1. It describes the details of the upcoming progress steps.
Moreover, the design process includes some sub process which will be described later.
Figure 1. Design Process
2.2. Laser Beam Detection in an Image
In order to validate image processing strategy for detection of laser light onto an image, first, a
device consisting of a webcam and a laser was used. With the help of the ideas presented in [10-13], the
initial processing was done in MATLAB. In Figure 2, the laser beam is projected almost to the bottom of the
image. As seen in this area, there is another red. It is possible that in this region, the laser dot appears as a
white dot that indicates the camera sensor is saturated. Thus, detecting White Laser Center from other parts
of the image is difficult and this is not possible unless using the RGB color value and the recognition of laser
light as a reference to the image processing system.
The result of an attempt to detect the laser light from pixels with the laser fringe color, is shown in
Figure 3. At this stage, process is only taken on the R part of each pixel of the image. In this case, some spots
are reported incorrectly as a pixel of laser boundary after processing of image. These false points leads the
Start
Characteristics
to measure the
distance
Hardware
Assembly
Assessing
the validity
of image
processing
algorithms
Solutions to
saturation
problem of
laser light in
the picture
Assessing
the validity
of image
processing
strategy
Mathematical
model of laser
distance
Validity
Test
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system to incorrectly reports the distance to the subject, which of course can cause a great loss to a system
which uses this report as its vision.
Figure 2. Laser light where there is a Possibility
of error
Figure 3. Result of Image Processing based on a
color Pixel
2.3. Solution of Light Saturation in the Image
To solve this problem, we should also consider the possibility of synthesis and implementation of
desired plan on FPGA. So, two simple solutions were implemented simultaneously to solve these problems.
a. RGB filtering according to specifications of laser light which is somewhat obtained by experimental and
repeated tests in MATLAB to separate the light with profile similar to that specifications.
b. Define an object with dimensions of laser light in the system and then filter the output of RGB filter
according to the dimensions of the object in order to exact separation of laser light in the picture.
By applying the provided solution to Figure 2, it is expected that the laser light in the image be
correctly detected. As seen in Figure 4, the laser is properly detected and shown as a white object.
The rest of pixels are converted to black, which reduces their impact on the next computation. As
seen in the Figures 2 and 3, with the fact that the center for laser and camera lens are in a direction, the
location of the laser light in the vertical direction of image has been estimated. Then, this section has been cut
off from main picture, so, less pixels of image will be sent to software for processing. Moreover, random
objects that are the same color as laser may be separated from the image. Also, for more accuracy of laser
light in the picture and to unit it as a standalone object, a series of filters have been used even to fill the cavity
inside the object. The result is shown on Figure 4.
Figure 4. Result of Applying RGB and other Filters
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2.4. The laser Detection Algorithm
A simple laser detection algorithm should be optimized to be implemented using the performance of
an embedded system which is limited compared to a personal computer. What a laser light detection
algorithm does in action is to scan image on the area where the laser light might be in order to find is laser
light. If the pixel color is in the range of the laser, it is converted to white, otherwise to black. Then, the white
pixels density is compared with each other and between them (if any) some range is reported as the laser light
which has the same density and size of laser beam (a few pixels that are located next to each other in a circle
form).
2.5. Laser Displacement Model, Based on the Barrier Distance
Up here, the laser light detection algorithm and its separation from image was provided. Now, a
solution should be presented to detect the distance to the object in front of the equipment. It is possible when
a mathematical model is presented to show the relation of the laser position on screen and real distance of
desired object to the equipment. This model is presented in Figure 5. To determine the distance, 5 following
parameters are introduced which are the main parameters of this connection.
dA: The minimum distance to an obstacle that can be detected by the camera. It can be calculated by
the following equation.
( ) ( )
(1)
dB: The maximum distance to an obstacle that can be detected by the camera. It can be calculated
by the following equation.
( ) ( )
(2)
D: Determine the distance between the obstacle and the camera. This value can be calculated from
the following equation.
( ( ) ( )) ( ( ))
(3)
Figure 5. The mathematical model for calculating the distance between the object and the camera
P: An auxiliary variable to show the ratio of the laser light in the image to the horizontal length of
whole image. It can be calculated from the following equation.
(4)
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L: A variable that indicates the actual length of the image at a distance d. It can be calculated from
the following equation.
( ) (5)
In these equations, l, represents the actual distance between the laser and the left boundary of the
image at a distance d, in fact, the same number that pops out of the image processing. Also, in this model, the
following equation should also be considered:
(6)
(7)
Finally, the value of X represents the distance between the center of the laser and the camera. The
results based on the mentioned parameters are presented in Figure 6. The results are presented in Figure 6
along with the corresponding parameters. Using these parameters, the values of the dA and dB were obtained
as .
The value of x is achieved by measuring the distance between the camera and the laser. Α is also
obtained by experimental simulation in MATLAB and β is presented to limit the maximum calculated
distance. In Figure 6, the x-axis is the number of pixels that the laser beam is located in and the y axis
indicates the distance to the desired object for each pixel of the image.
Figure 6. Comparison between the Actual distance and the Calculated distance in MATLAB.
The Parameters used are:
3. RESULTS AND ANALYSIS
3.1. The Performance of the MATLAB Simulator
The time consumption for processing a frame in MATLAB is about 80ms as shown in Figure 7.
Though this time seems to be sufficient to implement a real-time design, but for better real-time performance,
it is suggested to implement the proposed algorithm on some processors such as ARM, DSP or
FPGA [14-17]. However, for assessing the validity of image processing algorithms, MATLAB is an optimal
choice.
Finally, the performance of the proposed algorithm is compared with other methods in different
literatures. The result of this comparison is presented in Table 1. As can be seen, the proposed algorithm has
better distance measuring performance and accuracy versus other methods from different literatures. It should
be considered that some of these methods have also acceptable distance measuring performance such as [9].
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Figure 7. The processing time of an image frame in MATLAB
Table 1. Comparison of Distance Measuring Performance of Various Methods from Different Literatures
References
Accuracy rate of distance measurement
Up to
Method or device used
[3] (2001) 94% Ultrasound device
[4] (2005) 96% Rotating mirror
[5] (2009) 94.11% eye-distance
[6] (2009) 97.0% IR & Ultrasonic sensor
[7] (2010) 97.3% Modified Camera
[8] (2010) 97.1% Ultrasound sensor
[9] (2010) 99.48% cross correlation + ultrasound
Proposed methods 99.62%
Laser transmitter & CMOS
camera
3.2. The Performance of Camera and Laser
This device has good performance for indoor environments, factories, workshops, etc. which are
benefitting from favorable light. However, it should be said that the glass and mirror surfaces are known as
the system limits. In these cases, depending on how the laser light reflection occurs, the system may inform
the wrong distance or laser detection, which, as stated above, causes damage to the system used. In the case
of the environment with the light more than usual, it is difficult for the camera to detect the laser light and it
may reduce the maximum distance of obstacle detection which also means reducing the performance of the
system.
4. CONCLUSION
In this paper, an accurate and fast scheme for distance measurement based on laser optic was
presented. The proposed algorithm was presented to measure the distance from the object back to the camera.
The design can be implemented relatively simple, fast and inexpensive on various chips such as ARM or
FPGA. The run-time of one frame of the image was approximately 82 milliseconds. As shown, the accuracy
rate of distance measurement was up to 99.62%. Finally, comparing the proposed algorithm with some other
methods from different literatures proved the improved detection accuracy of the new scheme. This
technique can be used as robot vision to detect front objects and their distances for better react.
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BIOGRAPHY OF AUTHOR
Mohammad Hossein Doost Mohammadi
E-mail: doost.mohammadi@hut.ac.ir
M.H. DoostMohammadi obtained his M.Sc. degree from the Faculty of Electrical Engineering,
Iran University of Science and Technology. Since 2009, he has been Lecturer in Electrical
Engineering. Since 2011, he is a Lecturer with the Centers of Electrical and Biomedical
Engineering, Hamedan University of Technology, Iran. His interests are mainly Digital Signal
Processing and Digital Image Processing and their Implementation systems, especially FPGA.