A color-intensity feature extraction method is proposed aimed at supplementing conventional image hashing al-gorithms that only consider intensity of the image. An image is mapped to a set of blocks represented by their dominant principal colors more uniformly distributed. The average intensity is extracted from the Y component in the YCbCr space. By quantizing the color and intensity components, a feature vector is formed in a cylindrical coordinate system for each image to measure the degree of similarity between images in terms of the color-intensity features. This is used to validate effectiveness of the proposed feature vector. Experiments show that the color-intensity feature is robust to normal image processing while sensitive to malicious alteration,in particular,color modification.