Disparity map algorithm for stereo matching process using local based method

The aim of Stereo Vision Disparity Map (SVDM) algorithm is to obtain the disparity map from two images. These input images have different viewpoints that corresponds with each other, forming a two-dimensional mapping of matching pixels and is known as disparity map. The SVDM algorithm can be categor...

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Main Author:	Gan, Melvin Yeou Wei
Format:	Thesis
Language:	English English
Published:	2022
Subjects:	T Technology (General)
Online Access:	http://eprints.utem.edu.my/id/eprint/26881/1/Disparity%20map%20algorithm%20for%20stereo%20matching%20process%20using%20local%20based%20method.pdf http://eprints.utem.edu.my/id/eprint/26881/2/Disparity%20map%20algorithm%20for%20stereo%20matching%20process%20using%20local%20based%20method.pdf
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spelling	my-utem-ep.268812023-07-03T12:11:56Z Disparity map algorithm for stereo matching process using local based method 2022 Gan, Melvin Yeou Wei T Technology (General) TA Engineering (General). Civil engineering (General) The aim of Stereo Vision Disparity Map (SVDM) algorithm is to obtain the disparity map from two images. These input images have different viewpoints that corresponds with each other, forming a two-dimensional mapping of matching pixels and is known as disparity map. The SVDM algorithm can be categorized into local, semi global and global methods. Global method performs a matching process using global energy or a probability function over the whole image. This method involves high computational complexity and slow implementation. Therefore, it is not suitable for real-time applications. However, local method solves the matching problem via a local analysis and aggregating matching costs over a support region at each pixel in the images. The local method delivers fast execution and low computational requirement. Semi global method is the combination of both methods which make this method is more complex. However, the computation for the development of SVDM algorithm is more challenging especially for the images with complex scenes. There are several factors such as low texture region, repetitive patterns, illumination different, discontinuity, and occlusion. Hence, this thesis proposes a local-based SVDM algorithm that increases the accuracy on the complex scenes. The proposed SVDM algorithm involves four stages which starts from matching cost computation. At this stage, the proposed work uses the combination of Absolute Difference (AD) and Gradient Matching (GM) to produce the initial disparity map. Second stage, the Minimum Spanning Tree (MST) is utilised to remove noise from the initial disparity map. Then, the optimization stage uses a Winner-Take-All (WTA) strategy. The WTA strategy absorbs the minimal aggregated corresponding value for each valid pixel in disparity map. At the final stage, Bilateral Filter (BF) with Histogram Equalization and Weighted Median (WM) filter are proposed. These filters are capable to increase the accuracy and preserve the object edges. In this research, two standard online benchmarking database systems are used to measure the accuracy of the proposed algorithm. These systems are from the Middlebury Stereo for quantitative measurement and Karlsruhe Institute of Technology and Toyota Technological Institute (KITTI) for qualitative measurement. Once satisfactory results are obtained, there is demonstration on 3D surface reconstruction using disparity maps produced by the proposed SVDM algorithm. In conclusion, the proposed SVDM algorithm produces accurate results from the validation process. The final results are 7.55% for avg nonocc error and 10.6% for avg all error which are competitive with other established methods when compared in the standard benchmarking evaluation system from the Middlebury Stereo. The disparity map results on the complex scenes are also improved and fine quality of 3D surface reconstruction have been produced for both of the Middlebury and KITTI images. 2022 Thesis http://eprints.utem.edu.my/id/eprint/26881/ http://eprints.utem.edu.my/id/eprint/26881/1/Disparity%20map%20algorithm%20for%20stereo%20matching%20process%20using%20local%20based%20method.pdf text en public http://eprints.utem.edu.my/id/eprint/26881/2/Disparity%20map%20algorithm%20for%20stereo%20matching%20process%20using%20local%20based%20method.pdf text en validuser https://plh.utem.edu.my/cgi-bin/koha/opac-detail.pl?biblionumber=122215 mphil masters Universiti Teknikal Malaysia Melaka Faculty of Electrical Engineering Hamzah, Rostam Affendi
institution	Universiti Teknikal Malaysia Melaka
collection	UTeM Repository
language	English English
advisor	Hamzah, Rostam Affendi
topic	T Technology (General) T Technology (General)
spellingShingle	T Technology (General) T Technology (General) Gan, Melvin Yeou Wei Disparity map algorithm for stereo matching process using local based method
description	The aim of Stereo Vision Disparity Map (SVDM) algorithm is to obtain the disparity map from two images. These input images have different viewpoints that corresponds with each other, forming a two-dimensional mapping of matching pixels and is known as disparity map. The SVDM algorithm can be categorized into local, semi global and global methods. Global method performs a matching process using global energy or a probability function over the whole image. This method involves high computational complexity and slow implementation. Therefore, it is not suitable for real-time applications. However, local method solves the matching problem via a local analysis and aggregating matching costs over a support region at each pixel in the images. The local method delivers fast execution and low computational requirement. Semi global method is the combination of both methods which make this method is more complex. However, the computation for the development of SVDM algorithm is more challenging especially for the images with complex scenes. There are several factors such as low texture region, repetitive patterns, illumination different, discontinuity, and occlusion. Hence, this thesis proposes a local-based SVDM algorithm that increases the accuracy on the complex scenes. The proposed SVDM algorithm involves four stages which starts from matching cost computation. At this stage, the proposed work uses the combination of Absolute Difference (AD) and Gradient Matching (GM) to produce the initial disparity map. Second stage, the Minimum Spanning Tree (MST) is utilised to remove noise from the initial disparity map. Then, the optimization stage uses a Winner-Take-All (WTA) strategy. The WTA strategy absorbs the minimal aggregated corresponding value for each valid pixel in disparity map. At the final stage, Bilateral Filter (BF) with Histogram Equalization and Weighted Median (WM) filter are proposed. These filters are capable to increase the accuracy and preserve the object edges. In this research, two standard online benchmarking database systems are used to measure the accuracy of the proposed algorithm. These systems are from the Middlebury Stereo for quantitative measurement and Karlsruhe Institute of Technology and Toyota Technological Institute (KITTI) for qualitative measurement. Once satisfactory results are obtained, there is demonstration on 3D surface reconstruction using disparity maps produced by the proposed SVDM algorithm. In conclusion, the proposed SVDM algorithm produces accurate results from the validation process. The final results are 7.55% for avg nonocc error and 10.6% for avg all error which are competitive with other established methods when compared in the standard benchmarking evaluation system from the Middlebury Stereo. The disparity map results on the complex scenes are also improved and fine quality of 3D surface reconstruction have been produced for both of the Middlebury and KITTI images.
format	Thesis
qualification_name	Master of Philosophy (M.Phil.)
qualification_level	Master's degree
author	Gan, Melvin Yeou Wei
author_facet	Gan, Melvin Yeou Wei
author_sort	Gan, Melvin Yeou Wei
title	Disparity map algorithm for stereo matching process using local based method
title_short	Disparity map algorithm for stereo matching process using local based method
title_full	Disparity map algorithm for stereo matching process using local based method
title_fullStr	Disparity map algorithm for stereo matching process using local based method
title_full_unstemmed	Disparity map algorithm for stereo matching process using local based method
title_sort	disparity map algorithm for stereo matching process using local based method
granting_institution	Universiti Teknikal Malaysia Melaka
granting_department	Faculty of Electrical Engineering
publishDate	2022
url	http://eprints.utem.edu.my/id/eprint/26881/1/Disparity%20map%20algorithm%20for%20stereo%20matching%20process%20using%20local%20based%20method.pdf http://eprints.utem.edu.my/id/eprint/26881/2/Disparity%20map%20algorithm%20for%20stereo%20matching%20process%20using%20local%20based%20method.pdf
_version_	1776103150324809728

Disparity map algorithm for stereo matching process using local based method

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