Content-based Image Retrieval

The Creation of large multimedia information makes the content-based retrieval technology become a research focus. Content Based Image Retrieval (CBIR) means retrieving images based on the image content description features directly. The present research on CBIR focuses on the similarity-matching of lower-features, such as color, texture and shape.Color is basal element of image content and is one of the main sensing features for recognizing images. Color histogram is used widely for retrieving images, and the processing mostly concerns the choice and quantization of color space, the definition of color histogram and the distance of two points in color histogram space. This paper presents a method based on dividing-parts strategy and getting better retrieval results.Texture is an important image feature that is hard to describe. The analysis methods mostly include statistic method, structure method and frequency method. Gray scale co-existing matrix is an effective method for describing texture. This paper gives the procedure for retrieving images based on the characters extracted form it.Retrieval based on the object shape in an image is one of the most challenging problems in CBIR, because looking for the shape characters according with the human vision perception is not a simple work. Boundary and region are two aspects for describing shape. Most successful expression methods are Fruior Descriptors and Invariant Moments. The experiments show that seven Hu-Moments are invariant to displacement, rotation and scaling.Finally, we introduce the typical system framework of CBIR. Based on the survey, some open issues, which need to be researched further, are presented, and the future research trends are also given.