earticle

영어

With the development of society, number of art image becomes bigger and bigger. In order to classify the art images, it is necessary to retrieve the images with common features. Different from the commonly used image query method, art images are always seen by specific researchers and to study and classification, and it is much more important for the query method with high retrieval precision. So it is important to develop a better query method specifically used for the art image query. The main work of this paper is to establish a combined method to improve the art image query precision without decreasing the query time seriously. The combined query method includes several steps: (1) Initial query. The tag query method and the semantic query method will be used. The initial query results includes the results searched by both the methods. (2) Reorganization of the initial query results. The repeated images will be cleared and only one image will be left. (3) Distance based results rechecked. The most relative image will be ranked in front of the list and the less correlation image will be cleared. (4) Reordering the images. All the images will be reordered by the distance which reflects the correlation of the query image. According to the experimental verification, the combined method can improve the query precision.