Colour-Texture Fusion In Image Segmentation For Content-Based Image Retrieval Systems

Kemajuan teknologi komputer serta kepopularan World Wide Web telah membawa kepada peningkatan bilangan gambar yang berbentuk digital. Selari dengan perkembangan itu, sistem pencapaian imej berdasarkan kandungan (content-based image retrieval, CBIR) telah menjadi satu topic kajian yang berkembang...

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Main Author: Ooi , Woi Seng
Format: Thesis
Language:English
Published: 2007
Subjects:
Online Access:http://eprints.usm.my/31131/1/OOI_WOI_SENG.pdf
http://eprints.usm.my/31131/
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spelling my.usm.eprints.31131 http://eprints.usm.my/31131/ Colour-Texture Fusion In Image Segmentation For Content-Based Image Retrieval Systems Ooi , Woi Seng TK1-9971 Electrical engineering. Electronics. Nuclear engineering Kemajuan teknologi komputer serta kepopularan World Wide Web telah membawa kepada peningkatan bilangan gambar yang berbentuk digital. Selari dengan perkembangan itu, sistem pencapaian imej berdasarkan kandungan (content-based image retrieval, CBIR) telah menjadi satu topic kajian yang berkembang dengan pesatnya sejak kebelakangan ini. Proses segmentasi merupakan langkah prapemprosesan yang mempunyai pengaruh penting terhadap prestasi sistem CBIR. Oleh itu, dalam penyelidikan ini, satu rangka segmentasi imej yang baru, bersesuaian untuk pertanyaan kawasan (region queries) dalam CBIR, telah dipersembahkan. Teknik yang digunakan merupakan gabungan ciri-ciri warna dan tekstur gambar, dengan bantuan algoritma fuzzy c-means clustering (FCM) yang telah diubahsuai. With the advances in computer technologies and the popularity of the World Wide Web, the volume of digital images has grown rapidly. In parallel with this growth, content-based image retrieval (CBIR) is becoming a fast growing research area in recent years. Image segmentation is an important pre-processing step which has a great influence on the performance of CBIR systems. In this research, a novel image segmentation framework, dedicated to region queries in CBIR, is presented. The underlying technique is based on the fusion of colour and texture features by a modified fuzzy c-means clustering (FCM) algorithm. 2007-02 Thesis NonPeerReviewed application/pdf en http://eprints.usm.my/31131/1/OOI_WOI_SENG.pdf Ooi , Woi Seng (2007) Colour-Texture Fusion In Image Segmentation For Content-Based Image Retrieval Systems. Masters thesis, Universiti Sains Malaysia.
institution Universiti Sains Malaysia
building Hamzah Sendut Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Sains Malaysia
content_source USM Institutional Repository
url_provider http://eprints.usm.my/
language English
topic TK1-9971 Electrical engineering. Electronics. Nuclear engineering
spellingShingle TK1-9971 Electrical engineering. Electronics. Nuclear engineering
Ooi , Woi Seng
Colour-Texture Fusion In Image Segmentation For Content-Based Image Retrieval Systems
description Kemajuan teknologi komputer serta kepopularan World Wide Web telah membawa kepada peningkatan bilangan gambar yang berbentuk digital. Selari dengan perkembangan itu, sistem pencapaian imej berdasarkan kandungan (content-based image retrieval, CBIR) telah menjadi satu topic kajian yang berkembang dengan pesatnya sejak kebelakangan ini. Proses segmentasi merupakan langkah prapemprosesan yang mempunyai pengaruh penting terhadap prestasi sistem CBIR. Oleh itu, dalam penyelidikan ini, satu rangka segmentasi imej yang baru, bersesuaian untuk pertanyaan kawasan (region queries) dalam CBIR, telah dipersembahkan. Teknik yang digunakan merupakan gabungan ciri-ciri warna dan tekstur gambar, dengan bantuan algoritma fuzzy c-means clustering (FCM) yang telah diubahsuai. With the advances in computer technologies and the popularity of the World Wide Web, the volume of digital images has grown rapidly. In parallel with this growth, content-based image retrieval (CBIR) is becoming a fast growing research area in recent years. Image segmentation is an important pre-processing step which has a great influence on the performance of CBIR systems. In this research, a novel image segmentation framework, dedicated to region queries in CBIR, is presented. The underlying technique is based on the fusion of colour and texture features by a modified fuzzy c-means clustering (FCM) algorithm.
format Thesis
author Ooi , Woi Seng
author_facet Ooi , Woi Seng
author_sort Ooi , Woi Seng
title Colour-Texture Fusion In Image Segmentation For Content-Based Image Retrieval Systems
title_short Colour-Texture Fusion In Image Segmentation For Content-Based Image Retrieval Systems
title_full Colour-Texture Fusion In Image Segmentation For Content-Based Image Retrieval Systems
title_fullStr Colour-Texture Fusion In Image Segmentation For Content-Based Image Retrieval Systems
title_full_unstemmed Colour-Texture Fusion In Image Segmentation For Content-Based Image Retrieval Systems
title_sort colour-texture fusion in image segmentation for content-based image retrieval systems
publishDate 2007
url http://eprints.usm.my/31131/1/OOI_WOI_SENG.pdf
http://eprints.usm.my/31131/
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score 13.159002