Semantic Association Based Image Retrieve and Image Index

The challenges to content based image retrieve (CBIR) are various image retrieval requirements as well as the complex and hard described image content, and the gap between the digital array of image expression and the conceptual information universally accepted by human being. In this paper, a semantic association based image retrieve is proposed. Based on semantic association, a semantic representation vector for a scenic category is formed so that users can organize the similar images in perception together to form perceptional context and from which users can explain and mark images without need to give the connotation description for images. In addition, a kind of image neuron index method is proposed, which can speed up and guide the image or image block detection.