An automatic bleeding detection technique in wireless capsule endoscopy from region of interest

Abstract

Wireless capsule endoscopy (WCE) is a painless operative video technology to detect small intestine diseases, such as bleeding. Instead of using the most common RGB (red, green, blue) color scheme, in this paper, YIQ (luminance-Y, chrominance-IQ: in phase-I and quadrature-Q) color scheme is used for analyzing WCE video frames, which corresponds better to human color response characteristics. Analyzing the behavior of each of the four YIQ spaces, first, a region of interest is determined depending on the Q value of the pixels and some morphological operations. Next, instead of considering three spaces of YIQ color model separately, a new composite space Y.I/Q is proposed to capture intrinsic information about the luminance and chrominance of images. Four statistical measures, namely mean, median, skewness and minima of the pixel values in composite space within the ROI are computed as features. It is exhibited that use of composite space lower computational complexity as well as offers noticeably better discrimination between bleeding and non-bleeding pixels. For the purpose of classification, support vector machine (SVM) classifier is employed. Satisfactory bleeding detection performance result is achieved in terms of accuracy, sensitivity and specificity from severe experimentation on several WCE videos which is collected from a publicly available database. Also it is observed that proposed method over performs with comparing some of the existing methods.