Abstract
In this paper, a method for detecting possible presence of abnormality in the endoscopic images of lower esophagus is presented. The pre-processed endoscopic color images are segmented using color segmentation based on 3σ-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.
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© 2004 Springer-Verlag Berlin Heidelberg
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Hiremath, P.S., Dhandra, B.V., Hegadi, R., Rajput, G.G. (2004). Abnormality Detection in Endoscopic Images Using Color Segmentation and Curvature Computation. In: Pal, N.R., Kasabov, N., Mudi, R.K., Pal, S., Parui, S.K. (eds) Neural Information Processing. ICONIP 2004. Lecture Notes in Computer Science, vol 3316. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30499-9_128
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DOI: https://doi.org/10.1007/978-3-540-30499-9_128
Publisher Name: Springer, Berlin, Heidelberg
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