Color Image Retrieval Based on Primitives of Color Moments

In this paper, a color image retrieval method based on the primitives of color moments will be proposed. First, an image is divided into several blocks. Then, the color moments of all blocks are extracted and clustered into several classes. The mean moments of each class are considered as a primitive of the image. All primitives are used as features. Since two different images may have different numbers of features, a new similarity measure is then proposed. To demonstrate the effectiveness of the proposed method, two test databases from Corel are used to compare the performances of the proposed method with other existing ones. The experimental results show that the proposed method is usually better than others. Furthermore, since for few special types of images, other methods may have better results occasionally, a relevance feedback algorithm is also provided to automatically determine the best method according to the user’s response.