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A colour image retrieval method based on the primitives of colour moments is proposed. First, an image is divided into several blocks. Then, the colour 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 the others. Furthermore, since for a 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.