Co-occurrence features of multi-scale directional filter bank for texture charcterization

K. O. Cheng; Ngai Fong Law; W. C. Siu

Co-occurrence features of multi-scale directional filter bank for texture charcterization

K. O. Cheng
, Ngai Fong Law
, W. C. Siu

The Hong Kong Polytechnic University

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

2 Citations (Scopus)

Abstract

In this paper, we propose to use co-occurrence features computed from multi-scale directional Alter bank (MDFB) for texture characterization. As the Alter band coefficients are localized frequency components, features from co-occurrence matrices of filter bands can characterize structures of textures by describing correlation among coefficients. Our experiments show that the co-occurrence features outperform energy features considerably in texture retrieval. In particular, they significantly improve the retrieval rate for textures with weak directionality and periodicity while still maintain a high retrieval rate for regular textures as the energy features.

Original language	English
Title of host publication	ISCAS 2006
Subtitle of host publication	2006 IEEE International Symposium on Circuits and Systems, Proceedings
Pages	5499-5502
Number of pages	4
Publication status	Published - 1 Dec 2006
Event	ISCAS 2006: 2006 IEEE International Symposium on Circuits and Systems - Kos, Greece Duration: 21 May 2006 → 24 May 2006

Conference

Conference	ISCAS 2006: 2006 IEEE International Symposium on Circuits and Systems
Country/Territory	Greece
City	Kos
Period	21/05/06 → 24/05/06

ASJC Scopus subject areas

Electronic, Optical and Magnetic Materials
Electrical and Electronic Engineering

More information

http://hdl.handle.net/10397/283

Cite this

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title = "Co-occurrence features of multi-scale directional filter bank for texture charcterization",

abstract = "In this paper, we propose to use co-occurrence features computed from multi-scale directional Alter bank (MDFB) for texture characterization. As the Alter band coefficients are localized frequency components, features from co-occurrence matrices of filter bands can characterize structures of textures by describing correlation among coefficients. Our experiments show that the co-occurrence features outperform energy features considerably in texture retrieval. In particular, they significantly improve the retrieval rate for textures with weak directionality and periodicity while still maintain a high retrieval rate for regular textures as the energy features.",

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year = "2006",

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day = "1",

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isbn = "0780393902",

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Co-occurrence features of multi-scale directional filter bank for texture charcterization. / Cheng, K. O.; Law, Ngai Fong; Siu, W. C.
ISCAS 2006: 2006 IEEE International Symposium on Circuits and Systems, Proceedings. 2006. p. 5499-5502 1693879.

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

TY - GEN

T1 - Co-occurrence features of multi-scale directional filter bank for texture charcterization

AU - Cheng, K. O.

AU - Law, Ngai Fong

AU - Siu, W. C.

PY - 2006/12/1

Y1 - 2006/12/1

N2 - In this paper, we propose to use co-occurrence features computed from multi-scale directional Alter bank (MDFB) for texture characterization. As the Alter band coefficients are localized frequency components, features from co-occurrence matrices of filter bands can characterize structures of textures by describing correlation among coefficients. Our experiments show that the co-occurrence features outperform energy features considerably in texture retrieval. In particular, they significantly improve the retrieval rate for textures with weak directionality and periodicity while still maintain a high retrieval rate for regular textures as the energy features.

AB - In this paper, we propose to use co-occurrence features computed from multi-scale directional Alter bank (MDFB) for texture characterization. As the Alter band coefficients are localized frequency components, features from co-occurrence matrices of filter bands can characterize structures of textures by describing correlation among coefficients. Our experiments show that the co-occurrence features outperform energy features considerably in texture retrieval. In particular, they significantly improve the retrieval rate for textures with weak directionality and periodicity while still maintain a high retrieval rate for regular textures as the energy features.

UR - https://www.scopus.com/pages/publications/34547273264

M3 - Conference article published in proceeding or book

SN - 0780393902

SN - 9780780393905

SP - 5499

EP - 5502

BT - ISCAS 2006

T2 - ISCAS 2006: 2006 IEEE International Symposium on Circuits and Systems

Y2 - 21 May 2006 through 24 May 2006

ER -

Co-occurrence features of multi-scale directional filter bank for texture charcterization

Abstract

Conference

ASJC Scopus subject areas

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