In the US, colorectal cancer is the second leading cause of all cancer deaths behind lung cancer. Colorectal polyps are the precursor lesions of colorectal cancer. Therefore, early detection of polyps and at the same time removal of these precancerous lesions is one of the most important goals of colonoscopy. To objectively document detection and removal of colorectal polyps for quality purposes, and to facilitate real-time detection of polyps in the future, we have initiated a computer-based research program that analyzes video files created during colonoscopy. For computer-based detection of polyps, texture based techniques have been proposed. A major limitation of the existing texture-based analytical methods is that they depend on a fixed-size analytical window. Such a fixed-sized window may work for still images, but is not efficient for analysis of colonoscopy video files, where a single polyp can have different relative sizes and color features, depending on the viewing position and distance of the camera. In addition, the existing methods do not consider shape features. To overcome these problems, we here propose a novel polyp region segmentation method primarily based on the elliptical shape that nearly all small polyps and many larger polyps possess. Experimental results indicate that our proposed polyp detection method achieves a sensitivity and specificity of 93% and 98%, respectively.