Intestinal polyp recognition in capsule endoscopy images using color and shape features

Capsule endoscopy (CE) has gradually seen its wide application since it can directly view the small bowel in human body for the first time. However, a challenging problem is that too many images produced in each examination pose a tough workload to physicians. In this paper, we propose a new scheme aiming for intestinal polyp detection for CE images in order to partially solve this problem. This new scheme utilizes color and shape information, also powerful clues employed by physicians, to recognize polyp images. An illumination invariant color feature based on chromaticity histogram is first proposed. Integrating it with Zernike moments which are scale, translation and rotation invariant, we exploit the combined information as color and shape features to discriminate polyp from normal regions. Experiments on our present image data verify that it is promising to employ the proposed features to recognize polyp images.