Hybrid Region Merging For Image Segmentation Using Optimal Global Feature With Global Merging Criterion Approach

Region merging approach is used to reduce over segmented regions produced by region-based image segmentation algorithms. It is performed by merging the over segmented regions progressively to produce the final segmentation as spatially contiguous regions with closed boundaries. Predominantly, region...

Full description

Saved in:

Bibliographic Details
Main Author:	Vadiveloo, Mogana
Format:	Thesis
Language:	English
Published:	2020
Subjects:	QA75.5-76.95 Electronic computers Computer science
Online Access:	http://eprints.usm.my/55616/1/Pages%20from%20THESIS%20by%20MOGANA%20cut.pdf
Tags:	Add Tag No Tags, Be the first to tag this record!

id	my-usm-ep.55616
record_format	uketd_dc
spelling	my-usm-ep.556162022-11-11T02:00:32Z Hybrid Region Merging For Image Segmentation Using Optimal Global Feature With Global Merging Criterion Approach 2020-02 Vadiveloo, Mogana QA75.5-76.95 Electronic computers. Computer science Region merging approach is used to reduce over segmented regions produced by region-based image segmentation algorithms. It is performed by merging the over segmented regions progressively to produce the final segmentation as spatially contiguous regions with closed boundaries. Predominantly, region merging is performed between two neighboring regions solely on a local merging criterion. This may fail most existing region merging approaches to detect large non-homogeneous visual objects that have global semantic similarity but consist of diverse set of over segmented regions. Besides that, improper selection of global feature information by partitional clustering algorithm in turn affects the merging criterion derivation in region merging eventually causing leakages into adjacent visual object regions. Consequently, this thesis aims to solve these two issues by proposing a region merging approach to merge the over segmented regions producing semantic segments of visual objects regions. 2020-02 Thesis http://eprints.usm.my/55616/ http://eprints.usm.my/55616/1/Pages%20from%20THESIS%20by%20MOGANA%20cut.pdf application/pdf en public phd doctoral Universiti Sains Malaysia Pusat Pengajian Sains Komputer (School of Computer Sciences)
institution	Universiti Sains Malaysia
collection	USM Institutional Repository
language	English
topic	QA75.5-76.95 Electronic computers Computer science
spellingShingle	QA75.5-76.95 Electronic computers Computer science Vadiveloo, Mogana Hybrid Region Merging For Image Segmentation Using Optimal Global Feature With Global Merging Criterion Approach
description	Region merging approach is used to reduce over segmented regions produced by region-based image segmentation algorithms. It is performed by merging the over segmented regions progressively to produce the final segmentation as spatially contiguous regions with closed boundaries. Predominantly, region merging is performed between two neighboring regions solely on a local merging criterion. This may fail most existing region merging approaches to detect large non-homogeneous visual objects that have global semantic similarity but consist of diverse set of over segmented regions. Besides that, improper selection of global feature information by partitional clustering algorithm in turn affects the merging criterion derivation in region merging eventually causing leakages into adjacent visual object regions. Consequently, this thesis aims to solve these two issues by proposing a region merging approach to merge the over segmented regions producing semantic segments of visual objects regions.
format	Thesis
qualification_name	Doctor of Philosophy (PhD.)
qualification_level	Doctorate
author	Vadiveloo, Mogana
author_facet	Vadiveloo, Mogana
author_sort	Vadiveloo, Mogana
title	Hybrid Region Merging For Image Segmentation Using Optimal Global Feature With Global Merging Criterion Approach
title_short	Hybrid Region Merging For Image Segmentation Using Optimal Global Feature With Global Merging Criterion Approach
title_full	Hybrid Region Merging For Image Segmentation Using Optimal Global Feature With Global Merging Criterion Approach
title_fullStr	Hybrid Region Merging For Image Segmentation Using Optimal Global Feature With Global Merging Criterion Approach
title_full_unstemmed	Hybrid Region Merging For Image Segmentation Using Optimal Global Feature With Global Merging Criterion Approach
title_sort	hybrid region merging for image segmentation using optimal global feature with global merging criterion approach
granting_institution	Universiti Sains Malaysia
granting_department	Pusat Pengajian Sains Komputer (School of Computer Sciences)
publishDate	2020
url	http://eprints.usm.my/55616/1/Pages%20from%20THESIS%20by%20MOGANA%20cut.pdf
_version_	1776101099579637760

Hybrid Region Merging For Image Segmentation Using Optimal Global Feature With Global Merging Criterion Approach

Similar Items