关键词: 特征提取, 聚类, 语义分类, 图像检索

Abstract: In the light of the characteristic of large-scale patent image feature database, this paper uses the method of Bounding Box-Contour Distances（BBCD features） and block features to extract the low-lever visual features, and combines the algorithm of classify index based on K-means clustering, considering the semantic similitude and the visual features similitude, to construct the index structure of data in patent image database. Thus it achieves the retrieval after classify function. The result shows, this method can increase the search speed and improve the semantic sensitivity.

Key words: feature extraction, cluster, semantic classification, image retrieval