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초록
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.
키워드
Census transform; Image annotation; SVM; Census transform; Color and texture features; Digital image; Feature extraction and classification; Image annotation; Image color; Image semantics; Post processing; Research areas; SVM; SVM(support vector machine); Feature extraction; Image analysis; Image retrieval; Intelligent systems; Semantics; Surveys; Systems analysis; Principal component analysis
- 제목
- Image annotation using Principal component analysis of Census Transform
- 저자
- Hwang, Jungwon; Kim, Hyun Cheol; Kim, Whoi-Yul
- 발행일
- 2010-12
- 유형
- Conference Paper
- 저널명
- Proceedings of the 2010 10th International Conference on Intelligent Systems Design and Applications, ISDA'10
- 페이지
- 1259 ~ 1263