Research On Techniques Of Content Based Image Retrieval

Image database retrieval is one of the hot topic and has attracted increased attention from researchers. It includes several contents such as describing the image visual content, image database management, image matching and so on. This dissertation takes the image database retrieval as a master line, discusses the image retrieval method based on the visual content, proposes new image retrieval algorithms including algorithms based on the host tone multi-characteristic vector, the color and the spatial combination characteristic, the color and the texture combination characteristic, the shape characteristic and so on.Along with image database getting larger and larger, how to enhance the image retrieval efficiency has been become an urgent research issue. It is not able to yield a good result by using the sole image characteristic vector as image feature for inquiry. The retrieval proceding should get a satisfied balance between the rate of precision and the recall rate, in view of it, this dissertation proposed a new image retrieval method based on the multi-characteristic vector of color image, the features were extracted and processing on HSV color model and clustered to form different dimension characteristic vectors. A hierachical mapping schema with different dimension characteristic vectors is presented, which does enhance the image retrieval efficiency.To further upgrade the retrieval performance, a new kind of characteristic feature vector which is composed of color, intensity and spatial distribution information, is also proposed in this dissertation, the new features yield better retrieval results.Texture is an extremely important characteristic of images; however, it is not very efficient in pratical applications if only sololy using texture characteristics features. It is expected that the texture feature information is combined with color information, the information spatial distributions of colors and other visual information. This dissertalion proposes a new kind image retrieval method with combination of image color spatial distribution information and the texture characteristic. Firstly, the image was divided as several parts, then the regions connected with similar color were clustered, and the primitive co-occurrence matrix of four colors are extracted, finaly the image retrieval on the basis of the content is realized through using the feature similar criteroon which is designed according to these features.Since image retrieval based on shapes has long been one of the difficult problems in content based retrieval. The dissertation proposed a new kind image retrieval method based on shape content. First, a Canny operator is implemented to smooth the source image and get the feature of the edge direction histogram, then the improved invariant Moments are calculated for describing shape feature. These features are invariant under rotation, scale, translation and reflection of images and have been widely used in a number of application due to their invariance properties. In view of that the invariant moments focus on the distritntion of the region areas and in lower level reflects the shape contour characteristic, we propose a new method based on the integrated informations of invariant moments and edge direction.