Contour matching using ant colony optimization and curve evolution

Shape retrieval is a very important topic in computer vision. Image retrieval consists of selecting images that fulfil specific criteria from a collection of images. This thesis concentrates on contour-based image retrieval, in which we only explore the information located on the shape contour. T...

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Main Author:	Saadi, Younes
Format:	Thesis
Language:	English English English
Published:	2013
Subjects:	TA1501-1820 Applied optics Photonics
Online Access:	http://eprints.uthm.edu.my/2166/1/24p%20YOUNES%20SAADI.pdf http://eprints.uthm.edu.my/2166/2/YOUNES%20SAADI%20COPYRIGHT%20DECLARATION.pdf http://eprints.uthm.edu.my/2166/3/YOUNES%20SAADI%20WATERMARK.pdf
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id	my-uthm-ep.2166
record_format	uketd_dc
spelling	my-uthm-ep.21662021-10-31T02:59:18Z Contour matching using ant colony optimization and curve evolution 2013-01 Saadi, Younes TA1501-1820 Applied optics. Photonics Shape retrieval is a very important topic in computer vision. Image retrieval consists of selecting images that fulfil specific criteria from a collection of images. This thesis concentrates on contour-based image retrieval, in which we only explore the information located on the shape contour. There are many different kinds of shape retrieval methods. Most of the research in this field has till now concentrated on matching methods and how to achieve a meaningful correspondence. The matching process consist of finding correspondence between the points located on the designed contours. However, the huge number of incorporated points in the correspondence makes the matching process more complex. Furthermore, this scheme does not support computation of the correspondence intuitively without considering noise effect and distortions. Hence, heuristics methods are convoked to find acceptable solution. Moreover, some researches focus on improving polygonal modelling methods of a contour in such a way that the resulted contour is a good approximation of the original contour, which can be used to reduce the number of incorporated points in the matching. In this thesis, a novel approach for Ant Colony Optimization (ACO) contour matching that can be used to find an acceptable matching between contour shapes is developed. A polygonal evolution method proposed previously is selected to simplify the extracted contour. The main reason behind selecting this method is due to the use of a stopping criterion which must be predetermined. The match process is formulated as a Quadratic Assignment Problem (QAP) and resolved by using ACO. An approximated similarity is computed using original shape context descriptor and the Euclidean metric. The experimental results justify that the proposed approach is invariant to noise and distortions, and it is more robust to noise and distortion compared to the previously introduced Dominant Point (DP) Approach. 2013-01 Thesis http://eprints.uthm.edu.my/2166/ http://eprints.uthm.edu.my/2166/1/24p%20YOUNES%20SAADI.pdf text en public http://eprints.uthm.edu.my/2166/2/YOUNES%20SAADI%20COPYRIGHT%20DECLARATION.pdf text en staffonly http://eprints.uthm.edu.my/2166/3/YOUNES%20SAADI%20WATERMARK.pdf text en validuser mphil masters Universiti Tun Hussein Malaysia Fakulti Sains Komputer dan Teknologi Maklumat
institution	Universiti Tun Hussein Onn Malaysia
collection	UTHM Institutional Repository
language	English English English
topic	TA1501-1820 Applied optics Photonics
spellingShingle	TA1501-1820 Applied optics Photonics Saadi, Younes Contour matching using ant colony optimization and curve evolution
description	Shape retrieval is a very important topic in computer vision. Image retrieval consists of selecting images that fulfil specific criteria from a collection of images. This thesis concentrates on contour-based image retrieval, in which we only explore the information located on the shape contour. There are many different kinds of shape retrieval methods. Most of the research in this field has till now concentrated on matching methods and how to achieve a meaningful correspondence. The matching process consist of finding correspondence between the points located on the designed contours. However, the huge number of incorporated points in the correspondence makes the matching process more complex. Furthermore, this scheme does not support computation of the correspondence intuitively without considering noise effect and distortions. Hence, heuristics methods are convoked to find acceptable solution. Moreover, some researches focus on improving polygonal modelling methods of a contour in such a way that the resulted contour is a good approximation of the original contour, which can be used to reduce the number of incorporated points in the matching. In this thesis, a novel approach for Ant Colony Optimization (ACO) contour matching that can be used to find an acceptable matching between contour shapes is developed. A polygonal evolution method proposed previously is selected to simplify the extracted contour. The main reason behind selecting this method is due to the use of a stopping criterion which must be predetermined. The match process is formulated as a Quadratic Assignment Problem (QAP) and resolved by using ACO. An approximated similarity is computed using original shape context descriptor and the Euclidean metric. The experimental results justify that the proposed approach is invariant to noise and distortions, and it is more robust to noise and distortion compared to the previously introduced Dominant Point (DP) Approach.
format	Thesis
qualification_name	Master of Philosophy (M.Phil.)
qualification_level	Master's degree
author	Saadi, Younes
author_facet	Saadi, Younes
author_sort	Saadi, Younes
title	Contour matching using ant colony optimization and curve evolution
title_short	Contour matching using ant colony optimization and curve evolution
title_full	Contour matching using ant colony optimization and curve evolution
title_fullStr	Contour matching using ant colony optimization and curve evolution
title_full_unstemmed	Contour matching using ant colony optimization and curve evolution
title_sort	contour matching using ant colony optimization and curve evolution
granting_institution	Universiti Tun Hussein Malaysia
granting_department	Fakulti Sains Komputer dan Teknologi Maklumat
publishDate	2013
url	http://eprints.uthm.edu.my/2166/1/24p%20YOUNES%20SAADI.pdf http://eprints.uthm.edu.my/2166/2/YOUNES%20SAADI%20COPYRIGHT%20DECLARATION.pdf http://eprints.uthm.edu.my/2166/3/YOUNES%20SAADI%20WATERMARK.pdf
_version_	1747830917671419904

Contour matching using ant colony optimization and curve evolution

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