A New Personalized Image Classification Method
一种新的个性化的图象分类方法

Image classification system is an important part of any information retrieval system and pattern recognition system, and its key issue is to select some appropriate feature bindings of an image. Recent years content based image retrieval has been a very active research area. The dimension of the image feature vectors is normally very high and it's hard to index images. One of the main challenges in content based image retrieval is to develop techniques of performing dimension reduction. In this paper, a new model of searching multiple classification criterions has been proposed in which different feature bindings were formed to find new classification criterions, and a new algorithm was designed for this model. The experimental results shown that the proposed model can perform dimension reduction. The algorithm for the model is capable to reduce computational time which was also illustrated with results. The multiple criterions in combination with the information retrieval techniques can implement personalized information retrieval, and some results were given in last section.