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A New Pre-Processing Technique For Computational Of Stereo Matching Algorithm

This paper presents a new composition of stereo vision algorithm for disparity map measurement from matching process. Stereo colour images obtained are consists with noises due to undesirable weather and illumination conditions due to it taken under inadequate or non-uniform light. The algorithm be...

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Main Authors: Kadmin, Ahmad Fauzan, Hamzah, Rostam Affendi, Abd Manap, Nurulfajar, Hamid, Mohd Saad
Format: Article
Language:English
Published: Research Publication 2021
Online Access:http://eprints.utem.edu.my/id/eprint/25540/2/AMSJ-2021-N02-06%281%29.PDF
http://eprints.utem.edu.my/id/eprint/25540/
https://research-publication.com/wp-content/uploads/2021/vol-10-n02/AMSJ-2021-N02-06.pdf
https://doi.org/10.37418/amsj.10.2.6
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spelling my.utem.eprints.255402022-03-09T16:21:14Z http://eprints.utem.edu.my/id/eprint/25540/ A New Pre-Processing Technique For Computational Of Stereo Matching Algorithm Kadmin, Ahmad Fauzan Hamzah, Rostam Affendi Abd Manap, Nurulfajar Hamid, Mohd Saad This paper presents a new composition of stereo vision algorithm for disparity map measurement from matching process. Stereo colour images obtained are consists with noises due to undesirable weather and illumination conditions due to it taken under inadequate or non-uniform light. The algorithm begins with pre-processing stage to enhance the colour image quality using combination of CLAHE, AGCWD and guided filter. Then, the matching cost computation are done using the Census Transform that has a strong advantage in radial distortion and brightness changes. The third stage will produce the aggregated cost from matching process utilizing fixed-window and guided filter technique. At the fourth stage; disparity optimization stage, the disparity map is optimized with a common local technique, Winner-Take-All (WTA). Then, for final stage, the process continues with post processing that is Left Right (LR) consistency checking. Weighted Median (WM) filter is that applied to secure the final disparity map for noise reduction and smoothening to the disparity map. Based on Middlebury Standard Benchmarking Dataset, the proposed algorithm has 23.35% accuracy for nonocc error and 31.65% accuracy for all error, which yields a better accuracy compared to some works in the evaluation dataset. Research Publication 2021 Article PeerReviewed text en http://eprints.utem.edu.my/id/eprint/25540/2/AMSJ-2021-N02-06%281%29.PDF Kadmin, Ahmad Fauzan and Hamzah, Rostam Affendi and Abd Manap, Nurulfajar and Hamid, Mohd Saad (2021) A New Pre-Processing Technique For Computational Of Stereo Matching Algorithm. Advances in Mathematics: Scientific Journal, 10 (2). pp. 743-758. ISSN 1857-8365 https://research-publication.com/wp-content/uploads/2021/vol-10-n02/AMSJ-2021-N02-06.pdf https://doi.org/10.37418/amsj.10.2.6
institution Universiti Teknikal Malaysia Melaka
building UTEM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknikal Malaysia Melaka
content_source UTEM Institutional Repository
url_provider http://eprints.utem.edu.my/
language English
description This paper presents a new composition of stereo vision algorithm for disparity map measurement from matching process. Stereo colour images obtained are consists with noises due to undesirable weather and illumination conditions due to it taken under inadequate or non-uniform light. The algorithm begins with pre-processing stage to enhance the colour image quality using combination of CLAHE, AGCWD and guided filter. Then, the matching cost computation are done using the Census Transform that has a strong advantage in radial distortion and brightness changes. The third stage will produce the aggregated cost from matching process utilizing fixed-window and guided filter technique. At the fourth stage; disparity optimization stage, the disparity map is optimized with a common local technique, Winner-Take-All (WTA). Then, for final stage, the process continues with post processing that is Left Right (LR) consistency checking. Weighted Median (WM) filter is that applied to secure the final disparity map for noise reduction and smoothening to the disparity map. Based on Middlebury Standard Benchmarking Dataset, the proposed algorithm has 23.35% accuracy for nonocc error and 31.65% accuracy for all error, which yields a better accuracy compared to some works in the evaluation dataset.
format Article
author Kadmin, Ahmad Fauzan
Hamzah, Rostam Affendi
Abd Manap, Nurulfajar
Hamid, Mohd Saad
spellingShingle Kadmin, Ahmad Fauzan
Hamzah, Rostam Affendi
Abd Manap, Nurulfajar
Hamid, Mohd Saad
A New Pre-Processing Technique For Computational Of Stereo Matching Algorithm
author_facet Kadmin, Ahmad Fauzan
Hamzah, Rostam Affendi
Abd Manap, Nurulfajar
Hamid, Mohd Saad
author_sort Kadmin, Ahmad Fauzan
title A New Pre-Processing Technique For Computational Of Stereo Matching Algorithm
title_short A New Pre-Processing Technique For Computational Of Stereo Matching Algorithm
title_full A New Pre-Processing Technique For Computational Of Stereo Matching Algorithm
title_fullStr A New Pre-Processing Technique For Computational Of Stereo Matching Algorithm
title_full_unstemmed A New Pre-Processing Technique For Computational Of Stereo Matching Algorithm
title_sort new pre-processing technique for computational of stereo matching algorithm
publisher Research Publication
publishDate 2021
url http://eprints.utem.edu.my/id/eprint/25540/2/AMSJ-2021-N02-06%281%29.PDF
http://eprints.utem.edu.my/id/eprint/25540/
https://research-publication.com/wp-content/uploads/2021/vol-10-n02/AMSJ-2021-N02-06.pdf
https://doi.org/10.37418/amsj.10.2.6
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score 13.211869

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