DocumentCode :
2060668
Title :
Image annotation using Principal component analysis of Census Transform
Author :
Hwang, Jungwon ; Kim, HyunCheol ; Kim, Whoi-Yul
Author_Institution :
Dept. of Electron. & Comput. Eng., Hanyang Univ., Seoul, South Korea
fYear :
2010
fDate :
Nov. 29 2010-Dec. 1 2010
Firstpage :
1259
Lastpage :
1263
Abstract :
In this paper we propose the method that extracts the semantic keyword from digital images automatically using color and texture features. The image semantic keyword is widely used in research area like image retrieval, categorization, annotation, management. The method consists of two steps: feature extraction and classification module. In order to extract feature, the image color and PACT (Principal component analysis of Census Transform) histogram are used. For classification, SVM (Support Vector Machine) classifier is used. The final keyword is annotated after post-processing. Experimental results indicate that the proposed method can accurately extract the image semantic keywords.
Keywords :
demography; feature extraction; image retrieval; image texture; principal component analysis; support vector machines; SVM; digital image; feature classification; feature extraction; image annotation; image semantic keyword; principal component analysis of census transform; support vector machine; texture feature; Image annotation; SVM; census transform;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Systems Design and Applications (ISDA), 2010 10th International Conference on
Conference_Location :
Cairo
Print_ISBN :
978-1-4244-8134-7
Type :
conf
DOI :
10.1109/ISDA.2010.5687081
Filename :
5687081
Link To Document :
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