Image retrieval based on color and texture

Author

Guolei Wang ; Junding Sun

Author_Institution

Sch. of Comput. Sci. & Technol., Henan Polytech. Univ., Jiaozuo, China

fYear

2013

fDate

12-13 Oct. 2013

Firstpage

222

Lastpage

225

Abstract

A novel image retrieval algorithm based on color and texture is presented in the paper. Firstly, the entropy of each color component is computed as color feature based on block truncation coding (BTC). Then, the traditional gray level cooccurrence matrix (GLCM) is extended to neighbor statistic moment level co-occurrence matrix (MLCM), and then the texture feature is extracted based on MLCM. Finally, the weighted color and texture feature are fused together for image retrieval. Experimental results show that the proposed method get higher performance than the other methods mentioned in the paper.

Keywords

entropy; feature extraction; image coding; image colour analysis; image retrieval; image texture; matrix algebra; statistics; BTC; GLCM; MLCM; block truncation coding; color component entropy; color feature; gray level cooccurrence matrix; image retrieval algorithm; statistic moment level cooccurrence matrix; texture feature extraction; Accuracy; Color; Educational institutions; Feature extraction; Image coding; Image color analysis; Image retrieval; block truncation coding; content-based image retrieval; neighbor statistic MLCM;

fLanguage

English

Publisher

ieee

Conference_Titel

Computer Science and Network Technology (ICCSNT), 2013 3rd International Conference on

Conference_Location

Dalian

Type

conf

DOI

10.1109/ICCSNT.2013.6967100

Filename

6967100