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Title: Abnormality detection in endoscopic images using color segmentation and curvature computation
Authors: Hiremath P.S
Dhandra B.V
Hegadi R
Rajput G.G.
Issue Date: 2004
Citation: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) , Vol. 3316 , , p. 834 - 841
Abstract: In this paper, a method for detecting possible presence of abnormality in the endoscopic images of lower esophagus is presented. The preprocessed endoscopie color images are segmented using color segmentation based on 3?-intervals around mean RGB values. The zero-crossing method of edge detection is applied on the gray scale image corresponding to the segmented image. For the large contours, the Gaussian smoothing is performed for eliminating the noise in the curve. The curvature for each point of the curve is computed considering the support region of each point. The possible presence of abnormality is identified, when curvature of the contour segment between two zero crossing has the opposite curvature signs to those of such neighboring contour segments on the same edge contours. The experimental results show successful abnormality detection in the test images using this proposed method. © Springer-Verlag Berlin Heidelberg 2004.
Appears in Collections:1. Journal Articles

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