Abstract: A rough neural intelligent approach for rule generation and image classification is introduced.This method is a hybridization of intelligent computing techniques.Algorithms based on fuzzy image processing are first applied to enhance the contrast of the whole original image，to extract the region of interest and to enhance the edges surrounding that region.Then，this paper extracts features characterizing the underlying texture of the regions of interest by using the gray-level co-occurrence matrix.Then，the rough set approach to attribute reduction and rule generation is presented.Finally，rough neural network is designed for discrimination of different regions of interest to test whether they represent malignant cancer or benign cancer.To evaluate performance of the presented rough neural approach，this paper runs tests over different mammogram images.The experimental results show that the overall classification accuracy offered by rough neural approach is high compared with other intelligent techniques.