关键词: 感兴趣区域, 颜色直方图, 小波变换, 纹理特征, 图像相似度

Abstract: In this paper, a new method of content-based image retrieval is proposed, which is based on improved color and texture features based on wavelet transform. Traditional image retrieval can not reflect the extent of importance of different objects of retrieval images. Firstly it extracts some regions of interest of the image, and assigns weights to different sizes by different degrees of interest. Then it extracts color and texture features, and calculates the similarity of two images by three different methods, including location similarity, ROI and retrieval image, retrieval example image and retrieval image, and takes the maximum similarity as the final similarity of the two images; it sorts the similarity of retrieval sample image and retrieval image of the database by size, and chooses the most similar image as the search results. Experimental results show that the method improves the image retrieval performance, reflecting the personalized retrieval, which has a good effect.

Key words: region of interest, feature histogram, wavelet transform, texture features, image similarity