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Content-Based Image Retrieval through Improved Subblock Technique

Traditional Content-Based Image Retrieval (CBIR) systems mainly relied on the extraction of features globally. The drawback of this approach is that it cannot sufficiently capture the important features of individual regions in an image which users might be interested in. Due to that, an extensio...

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Main Author: Mustaffa, Mas Rina
Format: Thesis
Language:English
English
Published: 2006
Online Access:http://psasir.upm.edu.my/id/eprint/5196/1/FSKTM_2006_6.pdf
http://psasir.upm.edu.my/id/eprint/5196/
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spelling my.upm.eprints.51962013-05-27T07:21:05Z http://psasir.upm.edu.my/id/eprint/5196/ Content-Based Image Retrieval through Improved Subblock Technique Mustaffa, Mas Rina Traditional Content-Based Image Retrieval (CBIR) systems mainly relied on the extraction of features globally. The drawback of this approach is that it cannot sufficiently capture the important features of individual regions in an image which users might be interested in. Due to that, an extension of the CBIR systems is designed to exploit images at region or object level. One of the important tasks in CBIR at region or object level is to segment images into regions based on low-level features. Among the low-level features, colour and location information are widely used. In order to extract the colour information, Colour-based Dominant Region segmentation is used to extract a maximum of three dominant colour regions in an image together with its respective coordinates of the Minimum-Bounding Rectangle (MBR). The Sub-Block technique is then used to determine the location of the dominant regions by comparing the coordinates of the region’s MBR with the four corners of the centre of the location map. The cell number that is maximally covered by the region is supposedly to be assigned as the location index. However, the Sub- Block technique is not reliable because in most cases, the location index assigned is not the cell number that is maximally covered by the region and sometimes a region does not overlap with the cell number assigned at all. The effectiveness of this technique has been improved by taking into consideration the total horizontal and vertical distance of a region at each location where it overlaps. The horizontal distance from the left edge to the right edge of a region and the vertical distance from the top edge to the bottom edge of a region are calculated. The horizontal and vertical distances obtained for that region are then counted. The cell number with the highest distance would be assigned as the location index for that region. The individual colour and location index of each dominant region in an image is extended to provide combined colour-spatial indexes. During retrieval, images in the image database that have the same index as the query image is retrieved. A CBIR system implementing the Improved Sub-Block technique is developed. The CBIR system supports Query-By-Example (QBE). The retrieval effectiveness of the improved technique is tested through retrieval experiments on six image categories of about 900 images. The precision and recall is measured. From the experiments it is shown that retrieval effectiveness has been significantly improved by 85.86% through the Improved Sub-Block technique. 2006 Thesis NonPeerReviewed application/pdf en http://psasir.upm.edu.my/id/eprint/5196/1/FSKTM_2006_6.pdf Mustaffa, Mas Rina (2006) Content-Based Image Retrieval through Improved Subblock Technique. Masters thesis, Universiti Putra Malaysia. English
institution Universiti Putra Malaysia
building UPM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Putra Malaysia
content_source UPM Institutional Repository
url_provider http://psasir.upm.edu.my/
language English
English
description Traditional Content-Based Image Retrieval (CBIR) systems mainly relied on the extraction of features globally. The drawback of this approach is that it cannot sufficiently capture the important features of individual regions in an image which users might be interested in. Due to that, an extension of the CBIR systems is designed to exploit images at region or object level. One of the important tasks in CBIR at region or object level is to segment images into regions based on low-level features. Among the low-level features, colour and location information are widely used. In order to extract the colour information, Colour-based Dominant Region segmentation is used to extract a maximum of three dominant colour regions in an image together with its respective coordinates of the Minimum-Bounding Rectangle (MBR). The Sub-Block technique is then used to determine the location of the dominant regions by comparing the coordinates of the region’s MBR with the four corners of the centre of the location map. The cell number that is maximally covered by the region is supposedly to be assigned as the location index. However, the Sub- Block technique is not reliable because in most cases, the location index assigned is not the cell number that is maximally covered by the region and sometimes a region does not overlap with the cell number assigned at all. The effectiveness of this technique has been improved by taking into consideration the total horizontal and vertical distance of a region at each location where it overlaps. The horizontal distance from the left edge to the right edge of a region and the vertical distance from the top edge to the bottom edge of a region are calculated. The horizontal and vertical distances obtained for that region are then counted. The cell number with the highest distance would be assigned as the location index for that region. The individual colour and location index of each dominant region in an image is extended to provide combined colour-spatial indexes. During retrieval, images in the image database that have the same index as the query image is retrieved. A CBIR system implementing the Improved Sub-Block technique is developed. The CBIR system supports Query-By-Example (QBE). The retrieval effectiveness of the improved technique is tested through retrieval experiments on six image categories of about 900 images. The precision and recall is measured. From the experiments it is shown that retrieval effectiveness has been significantly improved by 85.86% through the Improved Sub-Block technique.
format Thesis
author Mustaffa, Mas Rina
spellingShingle Mustaffa, Mas Rina
Content-Based Image Retrieval through Improved Subblock Technique
author_facet Mustaffa, Mas Rina
author_sort Mustaffa, Mas Rina
title Content-Based Image Retrieval through Improved Subblock Technique
title_short Content-Based Image Retrieval through Improved Subblock Technique
title_full Content-Based Image Retrieval through Improved Subblock Technique
title_fullStr Content-Based Image Retrieval through Improved Subblock Technique
title_full_unstemmed Content-Based Image Retrieval through Improved Subblock Technique
title_sort content-based image retrieval through improved subblock technique
publishDate 2006
url http://psasir.upm.edu.my/id/eprint/5196/1/FSKTM_2006_6.pdf
http://psasir.upm.edu.my/id/eprint/5196/
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score 13.211869

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