A novel appearance-based method for person re-identification is proposed. The approach exploits three local features to extract the shape and the chromatic appearance of an individual. Robustness against low resolution images, viewpoint and illumination changes, occlusions and pose variations is achieved by a novel signature. A body part division is used to propose a novel distance measure. The method has been compared to state-of-the-art methods using a re-identification benchmark dataset. Results show that the proposed solution outperforms state-of-the-art methods used for comparison.