We propose an automatic image categorization technique for content-based image filtering and retrieval system. In this paper, category-feature database for image categorization is constructed on human visual perception. Query images are automatically classified into predefined categories by content-based description using MPEG-7. Similarity distances at each category are measured using multiple MPEG-7 descriptors. In this paper, a matching technique for combining multiple similarity distances is proposed. The proposed method takes into account the categorization performance of single descriptor at each category. To evaluate the proposed method, it is applied to a great number of query images randomly collected from the Internet and other image databases.