A novel similarity measure method for CBIR system

Authors:
Fenglian Liu
Affiliations:
School of Computer and Communication Engineering, Tianjin University of Technology, Tianjin, China and Tianjin Key Laboratory of Intelligence Computing and Novel Software Technology, Tianjin, Chin ...
Venue:
FSKD'09 Proceedings of the 6th international conference on Fuzzy systems and knowledge discovery - Volume 5
Year:
2009

Citing 2
Cited 0

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CBIR using Perception based Texture and Colour Measures

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Abstract

This paper presents a novel similarity measure method based a combination of color and texture feature representations. In this method, the YIQ color space is chosen, because it can describe both color images and gray images and the transform from RGB to YIQ is linear and simple than other color space. In the proposed method, we firstly segment image using texture feature by combination of wavelet transform and texture co-occurrence matrix and then quantize color feature in YIQ color space for every segmentation partition. Based on image segmentation and color quantization, a new kind of similarity measure is proposed. Compared with the traditional image retrieval methods, the proposed method is very efficient for the image retrieval purpose.