Improving Fractal Codes Based Image Retrieval Using Histogram of Collage Errors

Ming Hong Pi; Chong Sze Tong; Anup Basu

doi:10.1007/3-540-45113-7_13

Improving Fractal Codes Based Image Retrieval Using Histogram of Collage Errors

Ming Hong Pi^*, Chong Sze Tong, Anup Basu

^*Corresponding author for this work

Department of Mathematics

Research output: Chapter in book/report/conference proceeding › Conference proceeding › peer-review

7 Citations (Scopus)

Abstract

Collage error is a quantitative measure of the similarity between range block and "best-matching" domain block. It is relatively robust compared with the fractal encoding parameters which can be quite sensitive to changes in the domain block pool. However, up to now, fractal-based image indexing techniques are developed based on the fractal encoding parameters while collage error is overlooked. In the paper, we propose three composite statistical indices by combining histogram of fractal parameters with the histogram of collage errors to improve fractal codes based indexing technique. Experimental results on a database of 416 texture images show that the proposed indices not only reduce computational complexities, but also enhance the retrieval rate, compared to existing fractal-based retrieval methods.

Original language	English
Title of host publication	Image and Video Retrieval
Subtitle of host publication	Second International Conference, CIVR 2003 Urbana-Champaign, IL, USA, July 24–25, 2003 Proceedings
Editors	Erwin M. Bakker, Michael S. Lew, Thomas S. Huang, Nicu Sebe, Xiang Zhou
Publisher	Springer Berlin Heidelberg
Pages	121-130
Number of pages	10
Edition	1st
ISBN (Electronic)	9783540451136
ISBN (Print)	9783540406341
DOIs	https://doi.org/10.1007/3-540-45113-7_13
Publication status	Published - 24 Jun 2003
Event	2nd International Conference on Image and Video Retrieval CIVR 2003 - Urbana-Champaign, IL, United States Duration: 24 Jul 2003 → 25 Jul 2003

Publication series

Name	Lecture Notes in Computer Science
Volume	2728
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	2nd International Conference on Image and Video Retrieval CIVR 2003
Country/Territory	United States
City	Urbana-Champaign, IL
Period	24/07/03 → 25/07/03

Scopus Subject Areas

Theoretical Computer Science
General Computer Science

User-Defined Keywords

Composite Index
Texture Image
Query Image
Fractal Parameter
Retrieval Rate

Access to Document

10.1007/3-540-45113-7_13

Cite this

Pi, M. H., Tong, C. S., & Basu, A. (2003). Improving Fractal Codes Based Image Retrieval Using Histogram of Collage Errors. In E. M. Bakker, M. S. Lew, T. S. Huang, N. Sebe, & X. Zhou (Eds.), Image and Video Retrieval: Second International Conference, CIVR 2003 Urbana-Champaign, IL, USA, July 24–25, 2003 Proceedings (1st ed., pp. 121-130). (Lecture Notes in Computer Science; Vol. 2728). Springer Berlin Heidelberg. https://doi.org/10.1007/3-540-45113-7_13

Pi, Ming Hong ; Tong, Chong Sze ; Basu, Anup. / Improving Fractal Codes Based Image Retrieval Using Histogram of Collage Errors. Image and Video Retrieval: Second International Conference, CIVR 2003 Urbana-Champaign, IL, USA, July 24–25, 2003 Proceedings. editor / Erwin M. Bakker ; Michael S. Lew ; Thomas S. Huang ; Nicu Sebe ; Xiang Zhou. 1st. ed. Springer Berlin Heidelberg, 2003. pp. 121-130 (Lecture Notes in Computer Science).

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title = "Improving Fractal Codes Based Image Retrieval Using Histogram of Collage Errors",

abstract = "Collage error is a quantitative measure of the similarity between range block and {"}best-matching{"} domain block. It is relatively robust compared with the fractal encoding parameters which can be quite sensitive to changes in the domain block pool. However, up to now, fractal-based image indexing techniques are developed based on the fractal encoding parameters while collage error is overlooked. In the paper, we propose three composite statistical indices by combining histogram of fractal parameters with the histogram of collage errors to improve fractal codes based indexing technique. Experimental results on a database of 416 texture images show that the proposed indices not only reduce computational complexities, but also enhance the retrieval rate, compared to existing fractal-based retrieval methods.",

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author = "Pi, {Ming Hong} and Tong, {Chong Sze} and Anup Basu",

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Pi, MH, Tong, CS & Basu, A 2003, Improving Fractal Codes Based Image Retrieval Using Histogram of Collage Errors. in EM Bakker, MS Lew, TS Huang, N Sebe & X Zhou (eds), Image and Video Retrieval: Second International Conference, CIVR 2003 Urbana-Champaign, IL, USA, July 24–25, 2003 Proceedings. 1st edn, Lecture Notes in Computer Science, vol. 2728, Springer Berlin Heidelberg, pp. 121-130, 2nd International Conference on Image and Video Retrieval CIVR 2003, Urbana-Champaign, IL, United States, 24/07/03. https://doi.org/10.1007/3-540-45113-7_13

Improving Fractal Codes Based Image Retrieval Using Histogram of Collage Errors. / Pi, Ming Hong; Tong, Chong Sze; Basu, Anup.
Image and Video Retrieval: Second International Conference, CIVR 2003 Urbana-Champaign, IL, USA, July 24–25, 2003 Proceedings. ed. / Erwin M. Bakker; Michael S. Lew; Thomas S. Huang; Nicu Sebe; Xiang Zhou. 1st. ed. Springer Berlin Heidelberg, 2003. p. 121-130 (Lecture Notes in Computer Science; Vol. 2728).

Research output: Chapter in book/report/conference proceeding › Conference proceeding › peer-review

TY - GEN

T1 - Improving Fractal Codes Based Image Retrieval Using Histogram of Collage Errors

AU - Pi, Ming Hong

AU - Tong, Chong Sze

AU - Basu, Anup

PY - 2003/6/24

Y1 - 2003/6/24

N2 - Collage error is a quantitative measure of the similarity between range block and "best-matching" domain block. It is relatively robust compared with the fractal encoding parameters which can be quite sensitive to changes in the domain block pool. However, up to now, fractal-based image indexing techniques are developed based on the fractal encoding parameters while collage error is overlooked. In the paper, we propose three composite statistical indices by combining histogram of fractal parameters with the histogram of collage errors to improve fractal codes based indexing technique. Experimental results on a database of 416 texture images show that the proposed indices not only reduce computational complexities, but also enhance the retrieval rate, compared to existing fractal-based retrieval methods.

AB - Collage error is a quantitative measure of the similarity between range block and "best-matching" domain block. It is relatively robust compared with the fractal encoding parameters which can be quite sensitive to changes in the domain block pool. However, up to now, fractal-based image indexing techniques are developed based on the fractal encoding parameters while collage error is overlooked. In the paper, we propose three composite statistical indices by combining histogram of fractal parameters with the histogram of collage errors to improve fractal codes based indexing technique. Experimental results on a database of 416 texture images show that the proposed indices not only reduce computational complexities, but also enhance the retrieval rate, compared to existing fractal-based retrieval methods.

KW - Composite Index

KW - Texture Image

KW - Query Image

KW - Fractal Parameter

KW - Retrieval Rate

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SN - 9783540406341

T3 - Lecture Notes in Computer Science

SP - 121

EP - 130

BT - Image and Video Retrieval

A2 - Bakker, Erwin M.

A2 - Lew, Michael S.

A2 - Huang, Thomas S.

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PB - Springer Berlin Heidelberg

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ER -

Pi MH, Tong CS, Basu A. Improving Fractal Codes Based Image Retrieval Using Histogram of Collage Errors. In Bakker EM, Lew MS, Huang TS, Sebe N, Zhou X, editors, Image and Video Retrieval: Second International Conference, CIVR 2003 Urbana-Champaign, IL, USA, July 24–25, 2003 Proceedings. 1st ed. Springer Berlin Heidelberg. 2003. p. 121-130. (Lecture Notes in Computer Science). doi: 10.1007/3-540-45113-7_13

Improving Fractal Codes Based Image Retrieval Using Histogram of Collage Errors

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