Image Retrieval Based on Weighted Block Color Histogram and Texton Co-occurrece Matrix

DOI

10.2991/icitmi-15.2015.143How to use a DOI?

Keywords

image retrieval; HSV color histogram; texton co-occurrence matrix; feature extraction.

Abstract

Image retrieval is an important topic in the fields of image processing, pattern recognition and computer vision. In this paper, we proposed a new and efficient method of image retreival by combining the color and texture features. We used HSV color histogram for color feature extraction and texton co-occurrence matrix for texture feature extraction. In color feature extraction, the image was divided into nine unequal blocks first and then for each block HSV color histogram was computed. In texture feature extraction, the gray level image was filtered with four predefined textons first and then we used co-occurrence matrix to extract the texture feature of the filtered texton image. After feature extraction, we used Euclidean distance to measure the similarity of the query image and images in the database. We emploied Corel 1000 database for our experiment, the experimental results show that our proposed method performs better than the previous methods.

Copyright

© 2015, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Wenqing Huang
AU  - Jiazhe Dai
AU  - Qiang Wu
PY  - 2015/10
DA  - 2015/10
TI  - Image Retrieval Based on Weighted Block Color Histogram and Texton Co-occurrece Matrix
BT  - Proceedings of the 4th International Conference on Information Technology and Management Innovation
PB  - Atlantis Press
SP  - 848
EP  - 853
SN  - 2352-538X
UR  - https://doi.org/10.2991/icitmi-15.2015.143
DO  - 10.2991/icitmi-15.2015.143
ID  - Huang2015/10
ER  -