Image annotation using Principal component analysis of Census Transform

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.