DocumentCode :
3142903
Title :
Content-based image retrieval using approximate shape of objects
Author :
Traina, Agma J M ; Balan, Andre G R ; Bortolotti, Luis M. ; Traina, Caetano
Author_Institution :
Comput. Sci. Dept., Sao Paulo Univ., Sao Carlos, Brazil
fYear :
2004
fDate :
24-25 June 2004
Firstpage :
91
Lastpage :
96
Abstract :
This paper presents a new approach to retrieve images by content using a composition of relevant features regarding texture, shape and brightness distribution. The first step of the method is a segmentation process based on Markov random fields, which can be done automatically, having as parameter the number of desired classes. The regions obtained in the segmentation guide the extraction of measures from the original image producing a 30-dimensional feature vector used in the image retrieval. The experiments showed that the feature vector has high discrimination power and the time for retrieval operations are only fractions of seconds.
Keywords :
PACS; content-based retrieval; feature extraction; image colour analysis; image segmentation; image texture; medical image processing; 30-dimensional feature vector; Markov random fields; approximate object shape; brightness distribution; content-based image retrieval; extraction; image shape; image texture; segmentation process; Biomedical imaging; Brightness; Content based retrieval; Feature extraction; Histograms; Hospitals; Image retrieval; Image segmentation; Information retrieval; Shape;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer-Based Medical Systems, 2004. CBMS 2004. Proceedings. 17th IEEE Symposium on
ISSN :
1063-7125
Print_ISBN :
0-7695-2104-5
Type :
conf
DOI :
10.1109/CBMS.2004.1311697
Filename :
1311697
Link To Document :
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