DocumentCode :
3278472
Title :
Image classification by using a hybrid fractal-based method
Author :
An-Zen Shih ; Jheng-huei, Sie ; Kaiyang, Peng
Author_Institution :
Dept. of Inf. Technol., Jin-Wen Sci. & Technol. Univ., Taipei, Taiwan
Volume :
4
fYear :
2011
fDate :
10-13 July 2011
Firstpage :
1800
Lastpage :
1803
Abstract :
Content-based image retrieval (CBIR) has become one of the most interesting areas in the last decade. Many research works have been generated in this field, fn this paper we use a hybrid fractal-based method which incorporates vector quantization and relevance feedback to classify texture images. The experiment results suggest that our system is robust and efficient.
Keywords :
content-based retrieval; fractals; image classification; image retrieval; image texture; relevance feedback; vector quantisation; CBIR; content-based image retrieval; hybrid fractal-based method; relevance feedback; texture image classification; vector quantization; Fabrics; Fractals; Image segmentation; Lattices; Content-based image retrieval; Fractal;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Machine Learning and Cybernetics (ICMLC), 2011 International Conference on
Conference_Location :
Guilin
ISSN :
2160-133X
Print_ISBN :
978-1-4577-0305-8
Type :
conf
DOI :
10.1109/ICMLC.2011.6016991
Filename :
6016991
Link To Document :
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