Content-based Image Retrieval Combining Color And Spatial

In recent years,with the rapid development of Internet,the multimedia information is booming. All this information is mostly images. In the face of the immensity of information, people are eager to acquire information needed rapidly and efficiently. Effective recognizing, management and searching all these images have been an emergent problem.Most of the present image retrieval systems only concern the key word of the image description, neglecting another important element of image- the content of image. Content-Based Image Retrieval(CBIR)has been one of most active researches in multimedia technology and many research institutes have made great progress in this field. 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.Within Content-Based Image Retrieval, the color, being important vision information of image, has been used broadly. 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.In this dissertation, the exploratory research work has been done around the low-level feature extraction, which include color, shape,spatial features and so on. The main contributions of this dissertation are summarized as follows:1. Several key techniques and algorithms of CBIR are deeply analyzed and discussed, such as, color space, the low-level feature descriptions including color, shape, and texture, the similarity measure between the features and the evaluation methods of image retrieval algorithms.2. This paper proposes a new method combining color and spatial feature for efficient image retrieval. Color feature is extracted by the hue histogram of dominant colors. The image's H- ,S-,V- component are used to attain the image's spatial information. Experiments indicate that the synergy resulting from the combination of color and spatial is superior than using just color and spatial.