The X-ray chest image retrieval based on feature fusion

Author

Zhang, Quan ; Tai, Xiaoying

Author_Institution

Dept. of Comput. Sci., Ningbo Univ., Zhejiang

fYear

2008

fDate

7-9 July 2008

Firstpage

899

Lastpage

903

Abstract

Based on the analysis of methods of CBIR and chest image characteristic, in this paper, color correlogam, dominant color of partition, gray level co-occurrence matrix, gray-gradient co-occurrence matrix and shape invariant moments were extracted as retrieval feature. After comparison of their retrievals, feature fusion and relevance feedback is proposed. Experiments proved that the combining color, texture with shape feature gets effective retrieval and relevance feedback further more improves retrieval.

Keywords

content-based retrieval; feature extraction; image colour analysis; lung; matrix algebra; medical image processing; relevance feedback; X-ray chest image retrieval; color correlogam; content-based image retrieval; feature extraction; feature fusion; gray level cooccurrence matrix; gray-gradient cooccurrence matrix; relevance feedback; shape invariant moment; Biomedical imaging; Computer science; Feature extraction; Feedback; Frequency; Histograms; Image color analysis; Image retrieval; Shape; X-ray imaging;

fLanguage

English

Publisher

ieee

Conference_Titel

Audio, Language and Image Processing, 2008. ICALIP 2008. International Conference on

Conference_Location

Shanghai

Print_ISBN

978-1-4244-1723-0

Electronic_ISBN

978-1-4244-1724-7

Type

conf

DOI

10.1109/ICALIP.2008.4590166

Filename

4590166