Dynamic feature selection and coarse-to-fine search for content-based image retrieval

Jia You; Q. Li; K. H. Cheung; Prabir Bhattacharya

Dynamic feature selection and coarse-to-fine search for content-based image retrieval

Jia You, Q. Li, K. H. Cheung, Prabir Bhattacharya

Research output: Chapter in book / Conference proceeding › Conference article published in proceeding or book › Academic research › peer-review

Abstract

We present a new approach to content-based image retrieval by addressing three primary issues: image indexing, similarity measure, and search methods. The proposed algorithms include: an image data warehousing structure for dynamic image indexing; a statistically based feature selection procedure to form flexible similarity measures in terms of the dominant image features; and a feature component code to facilitate query processing and guide the search for the best matching. The experimental results demonstrate the feasibility and effectiveness of the proposed method.

Original language	English
Title of host publication	Proceedings of the 5th International Workshop on Pattern Recognition in Information Systems, PRIS 2005, in Conjunction with ICEIS 2005
Pages	81-93
Number of pages	13
Publication status	Published - 1 Dec 2005
Event	5th International Workshop on Pattern Recognition in Information Systems, PRIS 2005, in Conjunction with ICEIS 2005 - Miami, FL, United States Duration: 24 May 2005 → 25 May 2005

Conference

Conference	5th International Workshop on Pattern Recognition in Information Systems, PRIS 2005, in Conjunction with ICEIS 2005
Country/Territory	United States
City	Miami, FL
Period	24/05/05 → 25/05/05

ASJC Scopus subject areas

Computer Vision and Pattern Recognition
Information Systems

Cite this

@inproceedings{5ecee2f229b34715b1bd4987e0929911,

title = "Dynamic feature selection and coarse-to-fine search for content-based image retrieval",

abstract = "We present a new approach to content-based image retrieval by addressing three primary issues: image indexing, similarity measure, and search methods. The proposed algorithms include: an image data warehousing structure for dynamic image indexing; a statistically based feature selection procedure to form flexible similarity measures in terms of the dominant image features; and a feature component code to facilitate query processing and guide the search for the best matching. The experimental results demonstrate the feasibility and effectiveness of the proposed method.",

author = "Jia You and Q. Li and Cheung, {K. H.} and Prabir Bhattacharya",

year = "2005",

month = dec,

day = "1",

language = "English",

isbn = "9728865287",

pages = "81--93",

booktitle = "Proceedings of the 5th International Workshop on Pattern Recognition in Information Systems, PRIS 2005, in Conjunction with ICEIS 2005",

note = "5th International Workshop on Pattern Recognition in Information Systems, PRIS 2005, in Conjunction with ICEIS 2005 ; Conference date: 24-05-2005 Through 25-05-2005",

}

You, J, Li, Q, Cheung, KH & Bhattacharya, P 2005, Dynamic feature selection and coarse-to-fine search for content-based image retrieval. in Proceedings of the 5th International Workshop on Pattern Recognition in Information Systems, PRIS 2005, in Conjunction with ICEIS 2005. pp. 81-93, 5th International Workshop on Pattern Recognition in Information Systems, PRIS 2005, in Conjunction with ICEIS 2005, Miami, FL, United States, 24/05/05.

Dynamic feature selection and coarse-to-fine search for content-based image retrieval. / You, Jia; Li, Q.; Cheung, K. H. et al.
Proceedings of the 5th International Workshop on Pattern Recognition in Information Systems, PRIS 2005, in Conjunction with ICEIS 2005. 2005. p. 81-93.

Research output: Chapter in book / Conference proceeding › Conference article published in proceeding or book › Academic research › peer-review

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PY - 2005/12/1

Y1 - 2005/12/1

N2 - We present a new approach to content-based image retrieval by addressing three primary issues: image indexing, similarity measure, and search methods. The proposed algorithms include: an image data warehousing structure for dynamic image indexing; a statistically based feature selection procedure to form flexible similarity measures in terms of the dominant image features; and a feature component code to facilitate query processing and guide the search for the best matching. The experimental results demonstrate the feasibility and effectiveness of the proposed method.

AB - We present a new approach to content-based image retrieval by addressing three primary issues: image indexing, similarity measure, and search methods. The proposed algorithms include: an image data warehousing structure for dynamic image indexing; a statistically based feature selection procedure to form flexible similarity measures in terms of the dominant image features; and a feature component code to facilitate query processing and guide the search for the best matching. The experimental results demonstrate the feasibility and effectiveness of the proposed method.

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M3 - Conference article published in proceeding or book

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SP - 81

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BT - Proceedings of the 5th International Workshop on Pattern Recognition in Information Systems, PRIS 2005, in Conjunction with ICEIS 2005

T2 - 5th International Workshop on Pattern Recognition in Information Systems, PRIS 2005, in Conjunction with ICEIS 2005

Y2 - 24 May 2005 through 25 May 2005

ER -

Dynamic feature selection and coarse-to-fine search for content-based image retrieval

Abstract

Conference

ASJC Scopus subject areas

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