Integrating color and spatial features for content-based video retrieval

In this paper, we present a novel and efficient scheme for extracting, indexing and retrieving color images. Our motivation was to reduce the space overhead of partition-based approaches taking advantage of the fact that only a relatively low number of distinct values of a particular visual feature...

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Main Authors: LIN, Tong, NGO, Chong-wah, ZHANG, Hong-Jiang, SHI, Qing-Yun
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Language:English
Published: Institutional Knowledge at Singapore Management University 2001
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Online Access:https://ink.library.smu.edu.sg/sis_research/6534
https://ink.library.smu.edu.sg/context/sis_research/article/7537/viewcontent/icip01.pdf
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Institution: Singapore Management University
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spelling sg-smu-ink.sis_research-75372022-01-10T03:46:34Z Integrating color and spatial features for content-based video retrieval LIN, Tong NGO, Chong-wah ZHANG, Hong-Jiang SHI, Qing-Yun In this paper, we present a novel and efficient scheme for extracting, indexing and retrieving color images. Our motivation was to reduce the space overhead of partition-based approaches taking advantage of the fact that only a relatively low number of distinct values of a particular visual feature is present in most images. To extract color feature and build indices into our image database we take into consideration factors such as human color perception and perceptual range, and the image is partitioned into a set of regions by using a simple classifying scheme. The compact color feature vector and the spatial color histogram, which are extracted from the seqmented image region, are used for representing the color and spatial information in the image. We have also developed the region-based distance measures to compare the similarity of two images. Extensive tests on a large image collection were conducted to demonstrate the effectiveness of the proposed approach. 2001-10-01T07:00:00Z text application/pdf https://ink.library.smu.edu.sg/sis_research/6534 info:doi/10.1109/ICIP.2001.958188 https://ink.library.smu.edu.sg/context/sis_research/article/7537/viewcontent/icip01.pdf http://creativecommons.org/licenses/by-nc-nd/4.0/ Research Collection School Of Computing and Information Systems eng Institutional Knowledge at Singapore Management University Computer Sciences Graphics and Human Computer Interfaces
institution Singapore Management University
building SMU Libraries
continent Asia
country Singapore
Singapore
content_provider SMU Libraries
collection InK@SMU
language English
topic Computer Sciences
Graphics and Human Computer Interfaces
spellingShingle Computer Sciences
Graphics and Human Computer Interfaces
LIN, Tong
NGO, Chong-wah
ZHANG, Hong-Jiang
SHI, Qing-Yun
Integrating color and spatial features for content-based video retrieval
description In this paper, we present a novel and efficient scheme for extracting, indexing and retrieving color images. Our motivation was to reduce the space overhead of partition-based approaches taking advantage of the fact that only a relatively low number of distinct values of a particular visual feature is present in most images. To extract color feature and build indices into our image database we take into consideration factors such as human color perception and perceptual range, and the image is partitioned into a set of regions by using a simple classifying scheme. The compact color feature vector and the spatial color histogram, which are extracted from the seqmented image region, are used for representing the color and spatial information in the image. We have also developed the region-based distance measures to compare the similarity of two images. Extensive tests on a large image collection were conducted to demonstrate the effectiveness of the proposed approach.
format text
author LIN, Tong
NGO, Chong-wah
ZHANG, Hong-Jiang
SHI, Qing-Yun
author_facet LIN, Tong
NGO, Chong-wah
ZHANG, Hong-Jiang
SHI, Qing-Yun
author_sort LIN, Tong
title Integrating color and spatial features for content-based video retrieval
title_short Integrating color and spatial features for content-based video retrieval
title_full Integrating color and spatial features for content-based video retrieval
title_fullStr Integrating color and spatial features for content-based video retrieval
title_full_unstemmed Integrating color and spatial features for content-based video retrieval
title_sort integrating color and spatial features for content-based video retrieval
publisher Institutional Knowledge at Singapore Management University
publishDate 2001
url https://ink.library.smu.edu.sg/sis_research/6534
https://ink.library.smu.edu.sg/context/sis_research/article/7537/viewcontent/icip01.pdf
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