Modified Color Texton Histogram for Image Retrieval

被引：1

作者：

Qiu, Qin-Jun ^{[1
]}

Liu, Yong ^{[1
]}

Cai, Da-Wei ^{[1
]}

Tan, Jia-Zheng ^{[1
]}

机构：

[1] Three Gorges Univ, Yichang, Hubei Province, Peoples R China

来源：

2013 INTERNATIONAL CONFERENCE ON COMPUTER SCIENCES AND APPLICATIONS (CSA) | 2013年

关键词：

texton; image retrieval; texton histogram; the loc al structure detection; WAVELET CORRELOGRAM;

D O I：

10.1109/CSA.2013.142

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

In this paper, HSV based texton histogram (HSV-TH) is proposed for content based image retrieval (CBIR). The HSV-MT is proposed in contrast to the RGB based texton histogram (RGB-TH). The proposed HSV-TH method is based on Julesz's textons theory, and it works directly on nature images as shape descriptor and a color texture descriptor. HSV-TH integrates the advantages of co-occurrence matrix and histogram by representing the attribute of co-occurrence matrix using histogram. The retrieval results of the proposed method are tested on the different image databases i.e. Corel 1000 (DB1),Corel-10,000 (DB2) and MIT VisTex(DB3). Two experiments have been carried out for proving the worth of our algorithm. The results after being investigate show that a significant improvement in terms of their evaluation measures as compared to RGB-TH.

引用

页码：585 / 589

页数：5

共 18 条

[1]

Birgale L., 2006, INT C COMP GRAPH IM, P146, DOI DOI 10.1109/CGIV.2006.30

[2] Image retrieval: Ideas, influences, and trends of the new age [J].

Datta, Ritendra ;

Joshi, Dhiraj ;

Li, Jia ;

Wang, James Z. .

ACM COMPUTING SURVEYS, 2008, 40 (02)

[3] Increasing the discrimination power of the co-occurrence matrix-based features [J].

Gelzinis, A. ;

Verikas, A. ;

Bacauskiene, M. .

PATTERN RECOGNITION, 2007, 40 (09) :2367-2372

[4] Description of interest regions with local binary patterns [J].

Heikkila, Marko ;

Pietikainen, Matti ;

Schmid, Cordelia .

PATTERN RECOGNITION, 2009, 42 (03) :425-436

[5] Combining supervised learning with color correlograms for content-based image retrieval [J].

Huang, J ;

Kumar, SR ;

Mitra, M .

ACM MULTIMEDIA 97, PROCEEDINGS, 1997, :325-334

[6] Content based image retrieval using motif cooccurrence matrix [J].

Jhanwar, N ;

Chaudhuri, S ;

Seetharaman, G ;

Zavidovique, B .

IMAGE AND VISION COMPUTING, 2004, 22 (14) :1211-1220

[7] TEXTONS, THE ELEMENTS OF TEXTURE-PERCEPTION, AND THEIR INTERACTIONS [J].

JULESZ, B .

NATURE, 1981, 290 (5802) :91-97

[8] A survey on current content based image retrieval methods [J].

Kokare, M ;

Chatterji, BN ;

Biswas, PK .

IETE JOURNAL OF RESEARCH, 2002, 48 (3-4) :261-271

[9] Optimum Gabor filter design and local binary patterns for texture segmentation [J].

Li, Ma ;

Staunton, R. C. .

PATTERN RECOGNITION LETTERS, 2008, 29 (05) :664-672

[10] Image retrieval based on multi-texton histogram [J].

Liu, Guang-Hai ;

Zhang, Lei ;

Hou, Ying-Kun ;

Li, Zuo-Yong ;

Yang, Jing-Yu .

PATTERN RECOGNITION, 2010, 43 (07) :2380-2389

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