A Computational Approach to Edge Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
Highlight Removal by Illumination-Constrained Inpainting
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
Color Constancy
Machine Vision and Applications
Automatic segmentation and inpainting of specular highlights for endoscopic imaging
Journal on Image and Video Processing - Special issue on emerging methods for color image and video quality enhancement
Classifying color edges in video into shadow-geometry, highlight, or material transitions
IEEE Transactions on Multimedia
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Segmentation of specular reflections is an essential step in endoscopic image analysis; it affects all further processing steps including segmentation, classification, and registration tasks. The dichromatic reflectance model, which is often used for specular reflection modeling, is made for dielectric materials and not for human tissue. Hence, most recent segmentation approaches rely on thresholding techniques. In this work, we first demonstrate the limited accuracy that can be achieved by thresholding techniques and propose a hybridmethod which is based on closed contours and thresholding. The method has been evaluated on 269 specular reflections in 49 images which were taken from 27 real laparoscopic interventions. Ourmethod improves the average sensitivity by 16% compared to the state-of-the-art thresholding methods.