1) The document describes a novel design for an inexpensive high-quality panoramic camera. It uses a motor-controlled camera mounted on a 2-axis stand to capture overlapping images with recorded parameters for image stitching.
2) Simple image stitching algorithms along with recorded image parameters can be used to generate high-quality panoramic images in real-time, without requiring complicated computationally-intensive algorithms.
3) The proposed system was tested and able to produce high-quality stitched panoramic images using basic algorithms by controlling camera settings and overlap between images. This approach paves the way for low-cost portable panoramic camera systems.
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
Image fusion using nsct denoising and target extraction for visual surveillanceeSAT 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.
International journal of signal and image processing issues vol 2015 - no 1...sophiabelthome
This document reviews commonly used calibration patterns for camera calibration and image rectification. It discusses traditional 2D and 3D patterns using points, lines or geometric shapes. Structured light patterns using diffractive optical elements are also presented. Extraction of pattern data is important and can be done through intensity-based subpixel detection or edge detection techniques. Accuracy is evaluated using metrics like root mean square error. Image rectification transforms distorted images into rectilinear images by modeling and removing lens distortion.
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.
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.
International Journal of Computational Engineering Research(IJCER) ijceronline
nternational Journal of Computational Engineering Research (IJCER) is dedicated to protecting personal information and will make every reasonable effort to handle collected information appropriately. All information collected, as well as related requests, will be handled as carefully and efficiently as possible in accordance with IJCER standards for integrity and objectivity.
This document presents a conceptual design for an automated inspection system using image processing. The proposed system uses a flip drop mechanism to inspect aluminum blocks by weighing them, capturing an image, and using image processing software to match the block's pattern to a standard. If the weight and pattern match, the block is dropped into an acceptance center, and if not, into a rejection center. The document provides details on the system components, image processing steps, and compares the proposed design to other conceptual designs. It concludes the flip drop design is best suited for this application due to its compact size and limited moving parts.
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
Image fusion using nsct denoising and target extraction for visual surveillanceeSAT 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.
International journal of signal and image processing issues vol 2015 - no 1...sophiabelthome
This document reviews commonly used calibration patterns for camera calibration and image rectification. It discusses traditional 2D and 3D patterns using points, lines or geometric shapes. Structured light patterns using diffractive optical elements are also presented. Extraction of pattern data is important and can be done through intensity-based subpixel detection or edge detection techniques. Accuracy is evaluated using metrics like root mean square error. Image rectification transforms distorted images into rectilinear images by modeling and removing lens distortion.
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.
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.
International Journal of Computational Engineering Research(IJCER) ijceronline
nternational Journal of Computational Engineering Research (IJCER) is dedicated to protecting personal information and will make every reasonable effort to handle collected information appropriately. All information collected, as well as related requests, will be handled as carefully and efficiently as possible in accordance with IJCER standards for integrity and objectivity.
This document presents a conceptual design for an automated inspection system using image processing. The proposed system uses a flip drop mechanism to inspect aluminum blocks by weighing them, capturing an image, and using image processing software to match the block's pattern to a standard. If the weight and pattern match, the block is dropped into an acceptance center, and if not, into a rejection center. The document provides details on the system components, image processing steps, and compares the proposed design to other conceptual designs. It concludes the flip drop design is best suited for this application due to its compact size and limited moving parts.
ADVANCED ALGORITHMS FOR ETCHING SIMULATION OF 3D MEMS-TUNABLE LASERSijctcm
This document describes new algorithms for simulating etching in the fabrication of 3D microelectromechanical systems (MEMS) and MEMS-tunable lasers. The algorithms improve on existing 2D methods by applying boundary smoothing and remeshing after subtraction operations. They also use domain decomposition to more efficiently simulate etching of complex 3D structures by decomposing the structure into blocks. Numerical results demonstrating the algorithms' performance on realistic 3D MEMS and laser devices are presented and analyzed. The algorithms provide simple, robust simulations that significantly reduce runtimes for processing 3D MEMS and laser devices.
Photogrammetry is a scientific method that uses photography to reconstruct the 3D form and spatial position of objects from photographs. It involves acquiring images of an object from different positions and then using software to detect targets in the images and compute precise 3D coordinates. ICam systems are portable photogrammetry systems that employ triangulation to measure 3D coordinates of points on an object contactlessly using a digital camera, coded targets, and processing software. ICam offers high measurement accuracy down to 0.005mm and is suited for applications like inspection, deformation analysis, and crash testing.
Development of stereo matching algorithm based on sum of absolute RGB color d...IJECEIAES
This article presents local-based stereo matching algorithm which comprises a devel- opment of an algorithm using block matching and two edge preserving filters in the framework. Fundamentally, the matching process consists of several stages which will produce the disparity or depth map. The problem and most challenging work for matching process is to get an accurate corresponding point between two images. Hence, this article proposes an algorithm for stereo matching using improved Sum of Absolute RGB Differences (SAD), gradient matching and edge preserving filters. It is Bilateral Filter (BF) to surge up the accuracy. The SAD and gradient matching will be implemented at the first stage to get the preliminary corresponding result, then the BF works as an edge-preserving filter to remove the noise from the first stage. The second BF is used at the last stage to improve final disparity map and increase the object boundaries. The experimental analysis and validation are using the Middlebury standard benchmarking evaluation system. Based on the results, the proposed work is capable to increase the accuracy and to preserve the object edges. To make the proposed work more reliable with current available methods, the quantitative measurement has been made to compare with other existing methods and it shows the proposed work in this article perform much better.
IRJET - Steering Wheel Angle Prediction for Self-Driving CarsIRJET Journal
This document discusses using a convolutional neural network to predict steering wheel angle for self-driving cars. The network is trained using human driving data from a simulator. The network architecture includes convolutional and fully connected layers to map input images to steering angles. The network is evaluated in the simulator and is able to drive autonomously for periods of time without human intervention, demonstrating its ability to predict steering wheel angles needed for navigation.
Monitor and Quality Control for Automatic Production Line SystemIRJET Journal
1. The document describes a machine vision system developed to monitor and provide quality control for an automatic production line.
2. The system uses a camera and ultrasonic sensors to capture images and measure dimensions of product pieces on a conveyor belt. Computer vision and image processing algorithms are then used to analyze the images and determine if pieces meet manufacturing specifications.
3. Test results found the system could measure heights and diameters of pieces with an average error of 2.7% and 0.411 standard deviation, demonstrating the machine vision approach is a viable option for real-time quality control in industrial manufacturing applications.
Image morphing provides the tool to generate the flexible and powerful visual effect. Morphing depicts the transformation of one image into another image. The process of image morphing starts with the feature specification phase and then proceeds to warp generation phase, followed by the transition control phase. This paper surveys the various techniques available for all three stages of image morphing.
PARALLEL GENERATION OF IMAGE LAYERS CONSTRUCTED BY EDGE DETECTION USING MESSA...ijcsit
Edge detection is one of the most fundamental algorithms in digital image processing. Many algorithms have been implemented to construct image layers extracted from the original image based on selecting threshold parameters. Changing theses parameters to get a high quality layer is time consuming. In this paper, we propose two parallel technique, NASHT1 and NASHT2, to generate multiple layers of an input
image automatically to enable the image tester to select the highest quality detected edges. In addition, the
effect of intensive I/O operations and the number of parallel running processes on the performance of the proposed techniques have also been studied.
A study and comparison of different image segmentation algorithmsManje Gowda
This document discusses and compares different image segmentation algorithms. It begins with an introduction to the topic and an agenda that outlines image segmentation techniques, results and discussion, conclusions, and references. Section 2 describes various image segmentation techniques like thresholding, region-based (region growing and data clustering), and edge-based segmentation. Section 3 shows results of applying algorithms like Otsu's method, K-means clustering, quad tree, delta E, and FTH to sample images and compares their performance on simple versus complex images. The conclusion is that delta E performs best for simple images with one object, while for complex images with multiple objects, performance degrades and further work is needed.
MEDIAN BASED PARALLEL STEERING KERNEL REGRESSION FOR IMAGE RECONSTRUCTIONcsandit
Image reconstruction is a process of obtaining the original image from corrupted data.Applications of image reconstruction include Computer Tomography, radar imaging, weather forecasting etc. Recently steering kernel regression method has been applied for image reconstruction [1]. There are two major drawbacks in this technique. Firstly, it is computationally intensive. Secondly, output of the algorithm suffers form spurious edges(especially in case of denoising). We propose a modified version of Steering Kernel Regression called as Median Based Parallel Steering Kernel Regression Technique. In the proposed algorithm the first problem is overcome by implementing it in on GPUs and multi-cores. The second problem is addressed by a gradient based suppression in which median filter is used.Our algorithm gives better output than that of the Steering Kernel Regression. The results are compared using Root Mean Square Error(RMSE). Our algorithm has also shown a speedup of 21x using GPUs and shown speedup of 6x using multi-cores.
Median based parallel steering kernel regression for image reconstructioncsandit
Image reconstruction is a process of obtaining the original image from corrupted data.
Applications of image reconstruction include Computer Tomography, radar imaging, weather
forecasting etc. Recently steering kernel regression method has been applied for image
reconstruction [1]. There are two major drawbacks in this technique. Firstly, it is
computationally intensive. Secondly, output of the algorithm suffers form spurious edges
(especially in case of denoising). We propose a modified version of Steering Kernel Regression
called as Median Based Parallel Steering Kernel Regression Technique. In the proposed
algorithm the first problem is overcome by implementing it in on GPUs and multi-cores. The
second problem is addressed by a gradient based suppression in which median filter is used.
Our algorithm gives better output than that of the Steering Kernel Regression. The results are
compared using Root Mean Square Error(RMSE). Our algorithm has also shown a speedup of
21x using GPUs and shown speedup of 6x using multi-cores.
A Flexible Scheme for Transmission Line Fault Identification Using Image Proc...IJEEE
This paper describes a methodology that aims to find and diagnosing faults in transmission lines exploitation image process technique. The image processing techniques have been widely used to solve problem in process of all areas. In this paper, the methodology conjointly uses a digital image process Wavelet Shrinkage function to fault identification and diagnosis. In other words, the purpose is to extract the faulty image from the source with the separation and the co-ordinates of the transmission lines. The segmentation objective is the image division its set of parts and objects, which distinguishes it among others in the scene, are the key to have an improved result in identification of faults.The experimental results indicate that the proposed method provides promising results and is advantageous both in terms of PSNR and in visual quality.
The document describes a project submitted for a diploma in mechanical engineering. It discusses developing an automatic inspection system for machining components using machine vision. The system would use a camera and image processing software to inspect parts on a conveyor belt for defects. Defective parts would be ejected by a pneumatic cylinder controlled by a microcontroller and computer system. The project aims to develop industrial automation and quality control by automatically checking parts throughout the manufacturing process.
This document discusses techniques for enhancing thermal images, including converting to grayscale, histogram equalization, linear and adaptive filtering, and morphological operations. Histogram equalization spreads pixel intensities over the full range to improve contrast. Linear filtering is used for smoothing, sharpening and edge enhancement, while adaptive filtering better preserves edges. Morphological operations use a structuring element to quantify how well an element fits in an image. Fourier transforms change the image domain and can restore images through inverse transforms. The techniques can improve image quality for applications like quality control and diagnostics.
IRJET - Symmetric Image Registration based on Intensity and Spatial Informati...IRJET Journal
This document presents a proposed system for symmetric image registration based on intensity and spatial information using a technique called the Coloured Simple Algebraic Algorithm (CSAA). The system first preprocesses color images, extracts features, then classifies images as symmetric or asymmetric using a neural network. It is shown to provide accurate and robust registration of medical and biomedical images. The system is implemented and evaluated on sample images, demonstrating it can successfully identify symmetric versus asymmetric images. The proposed approach aims to improve on existing techniques for intensity-based image registration tasks.
IRJET-Vision Based Occupant Detection in Unattended VehicleIRJET Journal
This document proposes a vision-based method to detect and classify occupants inside an unattended vehicle using face recognition and motion-based classification. The system uses a camera mounted inside the vehicle to detect occupants in real-time at 30 frames per second with high accuracy under different lighting and weather conditions. It detects occupants in two steps - first detecting objects using background subtraction, then classifying objects as human or non-human using motion-based classification. The system aims to improve safety and comfort by monitoring occupants for applications like airbag deployment and climate control.
EMA3100A Target Motion Simulator User Guide - Chap1-IntroductionEngin Gul
EMA3100A Target Motion Simulator is a tool for generating target tracking data and modeling motions in 2D and 3D Cartesian and polar coordinates. It supports two main project types: Target Tracking Projects to generate tracking data for multiple targets, and Motion Modeling Projects to create trajectories from modeled paths. Projects can be created in different coordinate systems and consist of defining paths or targets, configuring sensors and measurements, and viewing simulated outputs. The simulator also provides standalone tools for path modeling, combining paths, viewing trajectories, and defining sensor measurements without creating a full project.
This document discusses single-GPU and multi-GPU implementations of the MAD IQA algorithm to improve its computational performance. A single-GPU implementation achieved a 24x speedup over the CPU version, bringing the runtime down to 40ms. A multi-GPU implementation using 3 GPUs achieved an additional speedup of 33x over the CPU version, bringing the runtime to 28.9ms, but required many more data transfers between GPUs and system memory. While parallelizing tasks across GPUs improved performance, latency from data transfers between devices limited gains.
Review on Optimal image fusion techniques and Hybrid techniqueIRJET Journal
This document reviews various image fusion techniques and proposes a hybrid technique. It discusses pixel-level, feature-level, and decision-level image fusion. Spatial domain methods like average fusion and temporal domain methods like discrete wavelet transform are described. The limitations of existing techniques like ringing artifacts and shift-variance are covered. A hybrid technique using set partitioning in hierarchical trees (SPIHT) and self-organizing migrating algorithm (SOMA) is proposed to improve fusion quality and efficiency over existing methods. This technique is presented as easier to implement and suitable for real-time applications.
1. A plane frame structure was modeled in GSA Suite software and analyzed under full factored loading. Bending moment diagrams were generated which identified maximum and minimum bending moments.
2. Hand calculations were shown to determine the global stiffness matrix partitions for the frame based on its degrees of freedom. The local stiffness matrix for a member was transformed to the global matrix.
3. Further analysis of the bending moment diagrams identified the locations of zero bending moments. For linear members, graphs were plotted and linear equations solved. Members with parabolic bending followed a quadratic equation to find two zero points.
Bariatric surgery, also known as weight loss surgery, includes procedures that reduce the size of the stomach or alter the small intestine to induce weight loss. The most common procedures are gastric bypass surgery, sleeve gastrectomy, and adjustable gastric banding. Bariatric surgery is recommended for patients with a body mass index (BMI) of at least 40, or 35 with serious comorbidities. It can result in significant long-term weight loss of 30-50% of excess body weight and reduction of obesity-related medical conditions. While generally effective, bariatric surgery carries risks of nutritional deficiencies, leaks, infections and other complications. Careful diet and lifestyle changes are important for success after surgery.
ADVANCED ALGORITHMS FOR ETCHING SIMULATION OF 3D MEMS-TUNABLE LASERSijctcm
This document describes new algorithms for simulating etching in the fabrication of 3D microelectromechanical systems (MEMS) and MEMS-tunable lasers. The algorithms improve on existing 2D methods by applying boundary smoothing and remeshing after subtraction operations. They also use domain decomposition to more efficiently simulate etching of complex 3D structures by decomposing the structure into blocks. Numerical results demonstrating the algorithms' performance on realistic 3D MEMS and laser devices are presented and analyzed. The algorithms provide simple, robust simulations that significantly reduce runtimes for processing 3D MEMS and laser devices.
Photogrammetry is a scientific method that uses photography to reconstruct the 3D form and spatial position of objects from photographs. It involves acquiring images of an object from different positions and then using software to detect targets in the images and compute precise 3D coordinates. ICam systems are portable photogrammetry systems that employ triangulation to measure 3D coordinates of points on an object contactlessly using a digital camera, coded targets, and processing software. ICam offers high measurement accuracy down to 0.005mm and is suited for applications like inspection, deformation analysis, and crash testing.
Development of stereo matching algorithm based on sum of absolute RGB color d...IJECEIAES
This article presents local-based stereo matching algorithm which comprises a devel- opment of an algorithm using block matching and two edge preserving filters in the framework. Fundamentally, the matching process consists of several stages which will produce the disparity or depth map. The problem and most challenging work for matching process is to get an accurate corresponding point between two images. Hence, this article proposes an algorithm for stereo matching using improved Sum of Absolute RGB Differences (SAD), gradient matching and edge preserving filters. It is Bilateral Filter (BF) to surge up the accuracy. The SAD and gradient matching will be implemented at the first stage to get the preliminary corresponding result, then the BF works as an edge-preserving filter to remove the noise from the first stage. The second BF is used at the last stage to improve final disparity map and increase the object boundaries. The experimental analysis and validation are using the Middlebury standard benchmarking evaluation system. Based on the results, the proposed work is capable to increase the accuracy and to preserve the object edges. To make the proposed work more reliable with current available methods, the quantitative measurement has been made to compare with other existing methods and it shows the proposed work in this article perform much better.
IRJET - Steering Wheel Angle Prediction for Self-Driving CarsIRJET Journal
This document discusses using a convolutional neural network to predict steering wheel angle for self-driving cars. The network is trained using human driving data from a simulator. The network architecture includes convolutional and fully connected layers to map input images to steering angles. The network is evaluated in the simulator and is able to drive autonomously for periods of time without human intervention, demonstrating its ability to predict steering wheel angles needed for navigation.
Monitor and Quality Control for Automatic Production Line SystemIRJET Journal
1. The document describes a machine vision system developed to monitor and provide quality control for an automatic production line.
2. The system uses a camera and ultrasonic sensors to capture images and measure dimensions of product pieces on a conveyor belt. Computer vision and image processing algorithms are then used to analyze the images and determine if pieces meet manufacturing specifications.
3. Test results found the system could measure heights and diameters of pieces with an average error of 2.7% and 0.411 standard deviation, demonstrating the machine vision approach is a viable option for real-time quality control in industrial manufacturing applications.
Image morphing provides the tool to generate the flexible and powerful visual effect. Morphing depicts the transformation of one image into another image. The process of image morphing starts with the feature specification phase and then proceeds to warp generation phase, followed by the transition control phase. This paper surveys the various techniques available for all three stages of image morphing.
PARALLEL GENERATION OF IMAGE LAYERS CONSTRUCTED BY EDGE DETECTION USING MESSA...ijcsit
Edge detection is one of the most fundamental algorithms in digital image processing. Many algorithms have been implemented to construct image layers extracted from the original image based on selecting threshold parameters. Changing theses parameters to get a high quality layer is time consuming. In this paper, we propose two parallel technique, NASHT1 and NASHT2, to generate multiple layers of an input
image automatically to enable the image tester to select the highest quality detected edges. In addition, the
effect of intensive I/O operations and the number of parallel running processes on the performance of the proposed techniques have also been studied.
A study and comparison of different image segmentation algorithmsManje Gowda
This document discusses and compares different image segmentation algorithms. It begins with an introduction to the topic and an agenda that outlines image segmentation techniques, results and discussion, conclusions, and references. Section 2 describes various image segmentation techniques like thresholding, region-based (region growing and data clustering), and edge-based segmentation. Section 3 shows results of applying algorithms like Otsu's method, K-means clustering, quad tree, delta E, and FTH to sample images and compares their performance on simple versus complex images. The conclusion is that delta E performs best for simple images with one object, while for complex images with multiple objects, performance degrades and further work is needed.
MEDIAN BASED PARALLEL STEERING KERNEL REGRESSION FOR IMAGE RECONSTRUCTIONcsandit
Image reconstruction is a process of obtaining the original image from corrupted data.Applications of image reconstruction include Computer Tomography, radar imaging, weather forecasting etc. Recently steering kernel regression method has been applied for image reconstruction [1]. There are two major drawbacks in this technique. Firstly, it is computationally intensive. Secondly, output of the algorithm suffers form spurious edges(especially in case of denoising). We propose a modified version of Steering Kernel Regression called as Median Based Parallel Steering Kernel Regression Technique. In the proposed algorithm the first problem is overcome by implementing it in on GPUs and multi-cores. The second problem is addressed by a gradient based suppression in which median filter is used.Our algorithm gives better output than that of the Steering Kernel Regression. The results are compared using Root Mean Square Error(RMSE). Our algorithm has also shown a speedup of 21x using GPUs and shown speedup of 6x using multi-cores.
Median based parallel steering kernel regression for image reconstructioncsandit
Image reconstruction is a process of obtaining the original image from corrupted data.
Applications of image reconstruction include Computer Tomography, radar imaging, weather
forecasting etc. Recently steering kernel regression method has been applied for image
reconstruction [1]. There are two major drawbacks in this technique. Firstly, it is
computationally intensive. Secondly, output of the algorithm suffers form spurious edges
(especially in case of denoising). We propose a modified version of Steering Kernel Regression
called as Median Based Parallel Steering Kernel Regression Technique. In the proposed
algorithm the first problem is overcome by implementing it in on GPUs and multi-cores. The
second problem is addressed by a gradient based suppression in which median filter is used.
Our algorithm gives better output than that of the Steering Kernel Regression. The results are
compared using Root Mean Square Error(RMSE). Our algorithm has also shown a speedup of
21x using GPUs and shown speedup of 6x using multi-cores.
A Flexible Scheme for Transmission Line Fault Identification Using Image Proc...IJEEE
This paper describes a methodology that aims to find and diagnosing faults in transmission lines exploitation image process technique. The image processing techniques have been widely used to solve problem in process of all areas. In this paper, the methodology conjointly uses a digital image process Wavelet Shrinkage function to fault identification and diagnosis. In other words, the purpose is to extract the faulty image from the source with the separation and the co-ordinates of the transmission lines. The segmentation objective is the image division its set of parts and objects, which distinguishes it among others in the scene, are the key to have an improved result in identification of faults.The experimental results indicate that the proposed method provides promising results and is advantageous both in terms of PSNR and in visual quality.
The document describes a project submitted for a diploma in mechanical engineering. It discusses developing an automatic inspection system for machining components using machine vision. The system would use a camera and image processing software to inspect parts on a conveyor belt for defects. Defective parts would be ejected by a pneumatic cylinder controlled by a microcontroller and computer system. The project aims to develop industrial automation and quality control by automatically checking parts throughout the manufacturing process.
This document discusses techniques for enhancing thermal images, including converting to grayscale, histogram equalization, linear and adaptive filtering, and morphological operations. Histogram equalization spreads pixel intensities over the full range to improve contrast. Linear filtering is used for smoothing, sharpening and edge enhancement, while adaptive filtering better preserves edges. Morphological operations use a structuring element to quantify how well an element fits in an image. Fourier transforms change the image domain and can restore images through inverse transforms. The techniques can improve image quality for applications like quality control and diagnostics.
IRJET - Symmetric Image Registration based on Intensity and Spatial Informati...IRJET Journal
This document presents a proposed system for symmetric image registration based on intensity and spatial information using a technique called the Coloured Simple Algebraic Algorithm (CSAA). The system first preprocesses color images, extracts features, then classifies images as symmetric or asymmetric using a neural network. It is shown to provide accurate and robust registration of medical and biomedical images. The system is implemented and evaluated on sample images, demonstrating it can successfully identify symmetric versus asymmetric images. The proposed approach aims to improve on existing techniques for intensity-based image registration tasks.
IRJET-Vision Based Occupant Detection in Unattended VehicleIRJET Journal
This document proposes a vision-based method to detect and classify occupants inside an unattended vehicle using face recognition and motion-based classification. The system uses a camera mounted inside the vehicle to detect occupants in real-time at 30 frames per second with high accuracy under different lighting and weather conditions. It detects occupants in two steps - first detecting objects using background subtraction, then classifying objects as human or non-human using motion-based classification. The system aims to improve safety and comfort by monitoring occupants for applications like airbag deployment and climate control.
EMA3100A Target Motion Simulator User Guide - Chap1-IntroductionEngin Gul
EMA3100A Target Motion Simulator is a tool for generating target tracking data and modeling motions in 2D and 3D Cartesian and polar coordinates. It supports two main project types: Target Tracking Projects to generate tracking data for multiple targets, and Motion Modeling Projects to create trajectories from modeled paths. Projects can be created in different coordinate systems and consist of defining paths or targets, configuring sensors and measurements, and viewing simulated outputs. The simulator also provides standalone tools for path modeling, combining paths, viewing trajectories, and defining sensor measurements without creating a full project.
This document discusses single-GPU and multi-GPU implementations of the MAD IQA algorithm to improve its computational performance. A single-GPU implementation achieved a 24x speedup over the CPU version, bringing the runtime down to 40ms. A multi-GPU implementation using 3 GPUs achieved an additional speedup of 33x over the CPU version, bringing the runtime to 28.9ms, but required many more data transfers between GPUs and system memory. While parallelizing tasks across GPUs improved performance, latency from data transfers between devices limited gains.
Review on Optimal image fusion techniques and Hybrid techniqueIRJET Journal
This document reviews various image fusion techniques and proposes a hybrid technique. It discusses pixel-level, feature-level, and decision-level image fusion. Spatial domain methods like average fusion and temporal domain methods like discrete wavelet transform are described. The limitations of existing techniques like ringing artifacts and shift-variance are covered. A hybrid technique using set partitioning in hierarchical trees (SPIHT) and self-organizing migrating algorithm (SOMA) is proposed to improve fusion quality and efficiency over existing methods. This technique is presented as easier to implement and suitable for real-time applications.
1. A plane frame structure was modeled in GSA Suite software and analyzed under full factored loading. Bending moment diagrams were generated which identified maximum and minimum bending moments.
2. Hand calculations were shown to determine the global stiffness matrix partitions for the frame based on its degrees of freedom. The local stiffness matrix for a member was transformed to the global matrix.
3. Further analysis of the bending moment diagrams identified the locations of zero bending moments. For linear members, graphs were plotted and linear equations solved. Members with parabolic bending followed a quadratic equation to find two zero points.
Bariatric surgery, also known as weight loss surgery, includes procedures that reduce the size of the stomach or alter the small intestine to induce weight loss. The most common procedures are gastric bypass surgery, sleeve gastrectomy, and adjustable gastric banding. Bariatric surgery is recommended for patients with a body mass index (BMI) of at least 40, or 35 with serious comorbidities. It can result in significant long-term weight loss of 30-50% of excess body weight and reduction of obesity-related medical conditions. While generally effective, bariatric surgery carries risks of nutritional deficiencies, leaks, infections and other complications. Careful diet and lifestyle changes are important for success after surgery.
This document provides information on percutaneous endoscopic gastrostomy (PEG) and jejunostomy procedures. It describes how PEG involves passing a feeding tube through the abdominal wall and into the stomach, and the indications for its use including when oral feeding is not adequate. Complications of PEG are outlined. Jejunostomy involves creating an opening from the abdomen directly into the jejunum, part of the small intestine, and its techniques and uses are discussed.
Dr. Jon Whitehurst - Bats, Maths and Maps - Nov 2016Simon Perry
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Similar to Novel-design-Panoramic-camera-by dr MONIKA (20)
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Novel-design-Panoramic-camera-by dr MONIKA
1. Novel design for Panoramic Camera
Dr Monika Jain Mr Dhiraj kr Sati
Professor Vice-President
Dept of Electronics & Instrumentation Engineering DPH Software Services Pvt Ltd.
Galgotias College of Engineering & Technology
Greater Noida
Nehru Place,
New Delhi
monika_jain24@rediffmail.com dksati@gmail.com
Ms Cuckoo Sati Mr Devarshi Bajpai
B.Tech, 4th
year B.Tech, 4th
year
Electronics and Instrumentation Engineering Electronics and Instrumentation Engineering
Galgotias College of Engineering & Technology
Greater Noida
Galgotias College of Engineering & Technology
Greater Noida
cuckoosati@gmail.com devarshi08@gmail.com
Ms Usha Tiwari
Assistant Professor
Dept of Electronics & Instrumentation Engineering
Galgotias College of Engineering & Technology
Greater Noida
ushapant@rediffmail.com
Abstract: In this paper, the design of the
inexpensive high quality panoramic camera has
been discussed. It has various applications in
biomedical, architectural, cartography, scanning
and other fields. With lowered costs, such systems
would have tremendous usage in many more
innovative applications. Though large amount of
research has been done on development of various
algorithms for seamless stitching of images still
some more aspects need to be explored. In this
sceneriao, rigorous work has been done on issues
that affect the quality of the stitched image and
also on the computational complexity of the
algorithms used to address those issues. Instead of
trying to resolve the issues with complicated
computation intensive algorithms, we worked on a
combination of hardware and less computation,
intensive approach to achieve high quality
panoramic pictures. In this paper it has been
demonstrated that image stitching can be
performed using routines and algorithms that
can operate in real time mode to generate
high quality panoramic images. This can be
done by using simple motor controlled camera
that records the parameters required for
image processing algorithms. It can be used
for testing and developing new algorithms.
These can be easily integrated into low cost camera
hardware for generating high quality panoramic
images on the fly.
Keywords: Image Processing, panoramic images,
I. INTRODUCTION
Image stitching is the process of combining
multiple photographic images with overlapping
fields of view to produce a segmented panorama
or high-resolution image. Commonly adopted
approaches to image stitching through the use of
computer software, require nearly exact overlaps
between images and identical exposures to
produce seamless results.
The steps in image stitching generally are as
follows:-
Creation of overlapped images
Motion Models
Image Registration
Blending
Extensive research has gone in each of these
steps. An important step is to establish the
mathematical relationships that can be used to
map pixel coordinates from one image to the
next.
The complexity of the mathematical models
depends on the way the pictures have been taken
and other image characteristics.
2. A. Motion Models
A wide variety of transforms such as simple
2D transforms, 3D transforms and their mapping
to non planar surfaces (e.g. cylindrical, spherical)
are used in the process. The commonly used
transformations are:
Translation
Rigid(Euclidean)
Similarity
Affine
Projective
Each of these translations preserves certain
characteristics of the image such as orientation,
lengths, angles, parallelism and straight lines.
B. Image Registration
One of the oldest and commonly used
algorithm is based on patch based alignment and
developed by Lucas and Kanade [1].
Sophisticated image registration algorithms have
been developed for medical imaging and remote
sensing applications by Goshtashby [2]. For
photogrammetry applications [8] manually
intensive methods based on ground control
points or manually registered tie points have
been used by Slama [3]. The globally consistent
solutions were achieved using the bundle
adjustment algorithm by Triggs et al. [4]. Many
researchers such as Davis [5], Uyttendaele et al.
[6], Agarwala et al. [7] has also presented in
globally consistent alignments and removal of
ghosts due to parallax and object movement.
Another class of algorithms is the feature based
algorithms by Brown et al and Badra et al [10-
11]. Both the above set of algorithms have the
ability to recognize panoramas among an
unordered set of pictures and can be used for
fully automated stitching. Fully automated
stitching algorithms are more computation
intensive and as the number of images increases
the processing requirements increase
significantly.
C. Blending
After identifying the image sequence, amount
of overlap a right blending technique is required
to blend the images seamlessly. Commonly used
blending techniques are laplacian pyramid
blending, gradient domain blending, exposure
compensation, high dynamic range imaging etc.
An alternative approach to motion-based de-
ghosting was proposed by Kang et al. [8], who
estimated dense optical flow between each input
image and a central reference image.
II. PROBLEM ANALYSIS
If various algorithms that are used in the
image stitching domain are looked upon, it is
observed that most of them are attempting to
tackle the issues arising out of images not
conducive to images stitching. Some of the
issues identified are as follows -
Images taken with excessive, low
overlap, undetermined overlap.
The images taken with cameras having,
barrel, pincushion, fisheye distortion.
Exposure differences in pictures taken
i.e. bias and gain.
Translational shift between two images.
Rotational shift between images.
Varying scales and aspect ratios of
images
Focal Length changes
Gaps and Overlaps
Parallax and moving objects
III. OUR APPROACH
Since a lot of research has already been done
in all the aspects of image stitching and proven
algorithms exist for different situations. To get
an accurately stitched image, the algorithms need
a set of pictures , picture parameters and the
desired result. These parameters are used to
identify the correct algorithm and to pass the
requisite parameters for an accurate result to be
used in a particular scenario. The parameters that
affect the choice of the algorithms have been
controlled and recorded. As all pictures are now
taken in a controlled environment with the
parameters recorded, the algorithms now do not
have to estimate the parameters governing their
operation. This implies that we can now select
the right algorithms and pass the right
parameters to them. As a result the images can
be stitched very accurately and the desired
panorama pictures can be produced.
The block diagram of the resulting system is
as shown in figure 1.
3. Figure 1.System Block Diagram
The camera is mounted on a 2 Axis stand
with 2 stepper motors controlling the movement
of the camera in X and Y axis. These steppers
motors are controlled with a computer where
motor speed and the angle of rotation increments
are defined. The camera settings can be adjusted
as desired either with a computer interface or by
directly using the buttons given on the camera .
The choices of parameters are determined by the
features desired in the stitched image. Proper
understanding of the algorithm and the effect on
the resultant image is required to set the
parameters accurately.
The various parameters used in taking the
pictures are recorded as Meta data within the
image or can even be stored as a part of the
filename of the image.
IV. EXPERIMENTAL SETUP
The setup consists of the following:-
Web cam
Camera mount
Regulated Power Supply-9V DC
Laptop
Many digital cameras have interface that can
control the focal length (zoom), aperture,
contrast and color compensation using a
computer interface.
A simple computer Interface was developed
in VB 6. The objective is to control the picture
quality, amount of over lap, eliminate gaps and
record the parameters to be passed on the image
stitching algorithms. This interface uses imaging
, webcam, controls to capture and display the
images. The information thus collected is used to
generate the suitable MATLAB code for
execution. The resultant file after processing in
MATLAB is then re input into the VB6 inteface
for visualization.
A. The camera stand
The camera is mounted on a stand as
depicted in figure 2. This allows for control
and movement of the camera in 2 –Axis.
Precise control and calibration of the
movement mechanism is done using stepper
motors and the vital parameters required for
stitching of images can be controlled and
recorded.
Figure 2. Camera Stand
B. The interface
The interface as designed in figure 3 allows
the user to control the image capture process and
to display the various pictures as they are taken
and also the resultant stitched image. The
pictures taken of our college (Galgotias College
of Engineering and Technology) were stitched
together to demonstrate the results.
4. Figure 3.Interface
C. Operation of the Camera
The camera settings are adjusted as per
requirement by clicking on the camera settings
button. Once the user starts the camera by
clicking on start camera the current image being
clicked is shown as in figure 4.
Figure 4.Camera Controller
The camera movement parameters can be set
as shown in the interface in figure 5 for each
axis. Consecutive pictures are taken and saved
into a folder as specified in the computer
interface.
Figure 5
The pictures thus taken are then stitched
using appropriate MATLAB functions.
MATLAB has an image processing library
which we have used to stitch the images. The
functions are used to calculate the Transform
Matrix, the RANSAC algorithm verifies that the
corners have been identified correctly and the
Mosaicking subsystem to overlay the frames
correctly.
Figure 6. Image after Stitching
V. RESULTS
Various pictures of moving and non moving
objects were taken and stitched together using
various algorithms and the resultant images were
analyzed. It was observed that with proper
settings of the camera, high quality results were
possible even with the simplest of the stitching
algorithms. When the seams of the images had
moving objects ghost images were observed. The
ghost images could be reduced by decreasing the
overlap when the pictures had moving objects
near the seams without using ghost removal
algorithms.
This essentially paves the way for developing
an inexpensive portable camera system that can
take panoramic images of high quality using
ordinary camera technology and simple image
stitching algorithms that can be integrated into a
low end microprocessor.
5. Sophisticated images of high quality can be
generated using multiple cameras controlled
centrally or over a network as in case of
recording of games. The pictures thus acquired
can be processed by more sophisticated
algorithms with cameras spread over various
physical positions.
VI. CONCLUSION
In this paper it has been demonstrated that
image stitching can be performed using routines
and algorithms that can operate in real time
mode to generate high quality panoramic images.
This can be done by using simple motor
controlled camera that records the parameters
required for image processing algorithms. It can
be used for testing and developing new
algorithms. In this paper various options have
been considered to work out a cost effective and
modular image stitching camera. The objective is
to establish a strong base for further refinement
and improvement in the image processing and
multidisciplinary applications of the technology.
Advances and refinements in camera technology
coupled with improvements in image processing
technology can easily be integrated into the
highly modular design of the system.
Large format projection, printing and
scanning applications will find great use of this
technology. Medical imaging costs can be
reduced significantly by extending concepts used
in this paper.
VII. REFERENCES
[1] Lucas, B. D. and Kanade, T.
(1981). An iterative image registration
technique with an application in stereo
vision. In Seventh International Joint
Conference on Artificial Intelligence
(IJCAI-81), pages 674–679, Vancouver.
[2] Goshtasby, A. (1989). Correction
of image deformation from lens
distortion using Bezier patches.
Computer Vision, Graphics, and Image
Processing, 47(4), 385–394.
[3] Slama, C. C., editor. (1980).
Manual of Photogrammetry. American
Society of Photogrammetry Falls Church,
Virginia, fourth edition.
[4] Triggs, B. et al.. (1999). Bundle
adjustment — a modern synthesis. In
International Workshop on Vision
Algorithms, pages 298–372, Springer,
Kerkyra, Greece.
[5] Davis, J. (1998). Mosaics of scenes
with moving objects. In IEEE Computer
Society Conference on Computer Vision
and Pattern Recognition (CVPR’98),
pages 354–360, Santa Barbara.73
[6] Uyttendaele, M., Eden, A., and
Szeliski, R. (2001). Eliminating ghosting
and exposure artifacts in image mosaics.
In IEEE Computer Society Conference
on Computer Vision and Pattern
Recognition (CVPR’2001), pages 509–
516, Kauai, Hawaii.
[7] Agarwala, A. et al.. (2005).
Panoramic video textures. ACM
Transactions on Graphics, 24(3), 821–
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[8] Frizot, Michael (ed.), 1998: Neue
Geschichte der Fotografie. Könemann
Verlagsgesellschaft, Köln.von Gruber, O.
(ed.), 1930: Ferienkurs in
Photogrammetry. Verlag Konrad
Wittwer, Stuttgart, 510p.
[9] Kang, S. B. et al.. (2003). High
dynamic range video. ACM Transactions
on Graphics, 22(3) 319–325. Seon Joo
Kim, Marc Pollefeys, "Robust
Radiometric Calibration and Vignetting
Correction," IEEE Transactions on
Pattern Analysis and Machine
Intelligence, Apr. 2008 vol. 30(4), pp.
562-576,
[10] Brown, M., Szeliski, R.,
andWinder, S. (2005). Multi-image
matching using multi-scale oriented
patches. In IEEE Computer Society
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Pattern Recognition(CVPR’2005), pages
510–517, San Diego, CA.
[11] Badra, F., Qumsieh, A., and Dudek,
G. (1998). Rotation and zooming in
image mosaicing. In IEEE Workshop on
Applications of Computer Vision
(WACV’98), pages 50–55, IEEE
Computer Society, Princeton