Depth map estimation using SIMULINK tool
01 Feb 2016-pp 332-336
TL;DR: The objective of the present work is to generate depth map using SIMULink tool and the SIMULINK model used to obtain depth map dataset images is presented.
Abstract: Stereo vision has usefulness in many applications like 3D scene reconstruction, robot navigation, etc. The disparity between two original stereo images and depth maps are calculated to find the depth levels. An algorithm to generate disparity maps using SIMULINK tool is presented in this paper. The disparity map was first obtained by using MATLAB tool. The objective of the present work is to generate depth map using SIMULINK tool. The SIMULINK model used to obtain depth map dataset images is presented.
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01 Oct 2019TL;DR: This research investigates an application of perceptive Vision-based offline programming assisted by visual cues to control a robotic arm in a hazardous and radioactive environment to ease the robot programming and fill the gap of operator absence in the workspace.
Abstract: Computer vision is one of the recent approaches used to increase robotic efficiency. Robotics has proved its effectiveness in working in radiation and nuclear environments in order to increase human safety. Nowadays, robots have become cheaper whereas the (re)programming and (re)training cost may exceed the robot installation cost. The current research investigates an application of perceptive Vision-based offline programming assisted by visual cues to control a robotic arm in a hazardous and radioactive environment to ease the robot programming and fill the gap of operator absence in the workspace. An experiment has been conducted to pick an object and place in a safe area. The position and orientation have been estimated without deep interference of the operator in mathematical calculation, visual feedback is provided to the operator, forward and inverse kinematics are calculated. A pick and place experiment has been conducted using MATLAB/SIMULINK program and embedded microcontroller system conducted to show the validity of the proposed system and prove its success.
1 citations
Cites methods from "Depth map estimation using SIMULINK..."
...NCC is usually used to overcome the problem of illumination change between the two cameras according to Equation 5[23-25]....
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References
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30 Sep 2010
TL;DR: Computer Vision: Algorithms and Applications explores the variety of techniques commonly used to analyze and interpret images and takes a scientific approach to basic vision problems, formulating physical models of the imaging process before inverting them to produce descriptions of a scene.
Abstract: Humans perceive the three-dimensional structure of the world with apparent ease. However, despite all of the recent advances in computer vision research, the dream of having a computer interpret an image at the same level as a two-year old remains elusive. Why is computer vision such a challenging problem and what is the current state of the art? Computer Vision: Algorithms and Applications explores the variety of techniques commonly used to analyze and interpret images. It also describes challenging real-world applications where vision is being successfully used, both for specialized applications such as medical imaging, and for fun, consumer-level tasks such as image editing and stitching, which students can apply to their own personal photos and videos. More than just a source of recipes, this exceptionally authoritative and comprehensive textbook/reference also takes a scientific approach to basic vision problems, formulating physical models of the imaging process before inverting them to produce descriptions of a scene. These problems are also analyzed using statistical models and solved using rigorous engineering techniques Topics and features: structured to support active curricula and project-oriented courses, with tips in the Introduction for using the book in a variety of customized courses; presents exercises at the end of each chapter with a heavy emphasis on testing algorithms and containing numerous suggestions for small mid-term projects; provides additional material and more detailed mathematical topics in the Appendices, which cover linear algebra, numerical techniques, and Bayesian estimation theory; suggests additional reading at the end of each chapter, including the latest research in each sub-field, in addition to a full Bibliography at the end of the book; supplies supplementary course material for students at the associated website, http://szeliski.org/Book/. Suitable for an upper-level undergraduate or graduate-level course in computer science or engineering, this textbook focuses on basic techniques that work under real-world conditions and encourages students to push their creative boundaries. Its design and exposition also make it eminently suitable as a unique reference to the fundamental techniques and current research literature in computer vision.
4,146 citations
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23 Jun 2008TL;DR: The proposed algorithm uses regions as matching primitives and defines the corresponding region energy functional for matching by utilizing the color statistics of regions and the constraints on smoothness and occlusion between adjacent regions.
Abstract: This paper presents a new stereo matching algorithm based on inter-regional cooperative optimization. The proposed algorithm uses regions as matching primitives and defines the corresponding region energy functional for matching by utilizing the color statistics of regions and the constraints on smoothness and occlusion between adjacent regions. In order to obtain a more reasonable disparity map, a cooperative optimization procedure has been employed to minimize the matching costs of all regions by introducing the cooperative and competitive mechanism between regions. Firstly, a color based segmentation method is used to segment the reference image into regions with homogeneous color. Secondly, a local window-based matching method is used to determine the initial disparity estimate of each image pixel. And then, a voting based plane fitting technique is applied to obtain the parameters of disparity plane corresponding to each image region. Finally, the disparity plane parameters of all regions are iteratively optimized by an inter-regional cooperative optimization procedure until a reasonable disparity map is obtained. The experimental results on Middlebury test set and real stereo images indicate that the performance of our method is competitive with the best stereo matching algorithms and the disparity maps recovered are close to the ground truth data.
320 citations
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TL;DR: A classical solution for matching two image patches is to use the cross-correlation coefficient, but this works well if there is a lot of structure within the patches, but not so well if the patches are close to uniform.
Abstract: Image correspondence and registration techniques have gained popularity in recent times due to advancement of utilization in digital media and its storage. The main problem associated with image processing is when it is applied to fields like robotic vision and machine vision. The problem is due to clutter, i.e. the same frame with different objects has to be matched. Hence there has been need for efficient techniques of Image Registration. This led to development of feature extraction techniques and template matching techniques. The normalized cross correlation technique is one of them. A classical solution for matching two image patches is to use the cross-correlation coefficient. This works well if there is a lot of structure within the patches, but not so well if the patches are close to uniform. This means that some patches are matched with more confidence than others. By estimating this uncertainty more weight can be put on the confident matches than those that are more uncertain. All the simulations have been performed using MATLAB tool.
52 citations
Additional excerpts
...NCC is even more complex to both SAD and SSD algorithms as it involves numerous multiplication, division and square root operations[4] primary interface is a graphical block diagramming tool and a customizable set of block libraries....
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01 Jan 2012
TL;DR: The architecture of filtering images for edge detection with the help of Video and Image Processing blockset is presented and the use of a tool with a high- level graphical interface under the Matlab Simulink based blocks which makes it very easy to handle with respect to other software.
Abstract: This Paper presents an efficient architecture for Image Segmentation. This architecture offers an alternative through a Graphical User Interface tool MATLAB. Image segmentation can be obtained by using various methods, but the drawback of most of the methods is that they use a high level language for coding. This paper focuses on processing an image pixel by pixel and in modification of pixel neighbourhoods that can be applied to the whole image. The objective lead to the use of a tool with a high- level graphical interface under the Matlab Simulink based blocks which makes it very easy to handle with respect to other software. The various applications where noise removal, enhancing edges and contours, blurring and so on. This paper presents the architecture of filtering images for edge detection with the help of Video and Image Processing blockset.
15 citations
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20 Jul 2014TL;DR: The present paper deals with the Transmitter-Receiver link for stereo images and movement of ROBOT proportional to estimated depth levels, and is a prototype which can be implemented for industrial applications.
Abstract: One of the promising application of wireless transmission is in Computer Vision. Real-time stereo images are captured using camera and transmitted to another system by using ZIGBEE wireless module. Before transmission, image pixels are grouped to form packets. These packets when received at the receiver end are recovered, and a 3-D image is generated. Also at the transmitter, images are segmented by using DPSO (Darwinian Particle Swarm Optimization). Segmented images are given to the line growing algorithm. Depth levels are estimated with the help of disparity values obtained from the disparity algorithm. These depth levels are transmitted through ZIGBEE module to another system. Depth levels received are used to control a ROBOT. This proposal is a prototype which can be implemented for industrial applications. The present paper deals with the Transmitter-Receiver link for stereo images and movement of ROBOT proportional to estimated depth levels. Keywords-ZIGBEE; Darwinian Particle Swarm Optimization; ROBOT.
2 citations