Hindawi Publishing Corporation EURASIP Journal on Image and Video Processing Volume 2010, Article ID 814319, 12 pages doi: Research Article Automatic Segmentation and Inpainting of Specular Highlights for Endoscopic Imaging Mirko Arnold, Anarta Ghosh, Stefan Ameling, and Gerard Lacey School of Computer Science and Statistics, Trinity College, Dublin, Ireland Correspondence should be addressed to Anarta Ghosh, aghosh@ Received 30 April 2010; Revised 2 November 2010; Accepted 2 December 2010 Academic Editor: Sebastiano Battiato Copyright © 2010 Mirko Arnold et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium,. | Hindawi Publishing Corporation EURASIP Journal on Image and Video Processing Volume 2010 Article ID814319 12 pages doi 2010 814319 Research Article Automatic Segmentation and Inpainting of Specular Highlights for Endoscopic Imaging Mirko Arnold Anarta Ghosh Stefan Ameling and Gerard Lacey School of Computer Science and Statistics Trinity College Dublin Ireland Correspondence should be addressed to Anarta Ghosh aghosh@ Received 30 April 2010 Revised 2 November 2010 Accepted 2 December 2010 Academic Editor Sebastiano Battiato Copyright 2010 Mirko Arnold et al. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use distribution and reproduction in any medium provided the original work is properly cited. Minimally invasive medical procedures have become increasingly common in today s healthcare practice. Images taken during such procedures largely show tissues of human organs such as the mucosa of the gastrointestinal tract. These surfaces usually have a glossy appearance showing specular highlights. For many visual analysis algorithms these distinct and bright visual features can become a significant source of error. In this article we propose two methods to address this problem a a segmentation method based on nonlinear filtering and colour image thresholding and b an efficient inpainting method. The inpainting algorithm eliminates the negative effect of specular highlights on other image analysis algorithms and also gives a visually pleasing result. The methods compare favourably to the existing approaches reported for endoscopic imaging. Furthermore in contrast to the existing approaches the proposed segmentation method is applicable to the widely used sequential RGB image acquisition systems. 1. Introduction Due to reduced patient recovery time and mortality rate minimally invasive medical procedures have become increasingly common in today s healthcare practice. Consequently .
