A NEW METHOD OF MEDICAL IMAGE RETRIEVAL BASED ON COLOR–TEXTURE CORRELOGRAM AND GTI MODEL

Xiao-Ying Tai, Li-Dong Wang, Qin Chen, Ren Fuji () and Kita Kenji
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Xiao-Ying Tai: Institute of Information Science and Engineering, Ningbo University, Zhejiang 315211, China
Li-Dong Wang: Qianjiang College, Hangzhou Normal University, Zhejiang 310012, China
Qin Chen: Institute of Information Science and Engineering, Ningbo University, Zhejiang 315211, China
Ren Fuji: Faculty of Engineering, The University of Tokushima, Tokushima 770-8506, Japan
Kita Kenji: Center for Advanced Information Technology, The University of Tokushima, Tokushima 770-8506, Japan

International Journal of Information Technology & Decision Making (IJITDM), 2009, vol. 08, issue 02, 239-248

Abstract: This paper presents a method for endoscopic image retrieval based on color–texture correlogram and Generalized Tversky's Index (GTI) model. First we define a new image feature named color–texture correlogram, which is the extension of color correlogram. The texture image extracted by texture spectrum algorithm is combined with color feature vector, and then we calculate the spatial correlation of color–texture feature vector. Similarity metric is also the key technology during domain of image retrieval, GTI model is used in medical image retrieval for similarity metric, and the technique of relevance feedback is used in the algorithm to enhance the efficiency of retrieval. Experimental results show that the method discussed in this paper is much more effective.

Keywords: Medical image retrieval; endoscopic images; color correlogram; texture spectrum; color–texture correlogram; GTI model (search for similar items in EconPapers)
Date: 2009
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Citations: View citations in EconPapers (1)

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DOI: 10.1142/S0219622009003363

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