Image Retrieval via Relevance Vector Machine with Multiple Features

With the fast development of computer network technique, there is large amount of image information every day. Researchers have paid more and more attention to the problem of how users quickly retrieving and identifying the images that they may interest. Meanwhile, with the rapid development of artificial intelligence and pattern recognition techniques, it provides people with new thought on the study on complex image retrieval while it’s very difficult for traditional machine learning method to get ideal retrieval results. For this reason, we in this paper propose a new approach for image retrieval based on multiple types of image features and relevance vector machine (RVM). The proposed method, termed as MF-RVM, integrates the informative cures of features and the discrimination ability of RVM. The retrieval experiment is conducted on COREL image library which is collected from internet. The experimental results show that the proposed method can significantly improve the performance for image retrieval, so MF-RVM presented in this paper has very high practicability in image retrieval.