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Detection of grey regions in color images : application to the segmentation of a surgical instrument in robotized laparoscopy

In this paper, the detection and localization of grey regions in color images is addressed. This work has been developed in the scope of the robotized laparoscopic surgery, specifically for surgical procedures occurring inside the abdominal cavity. Since very few works have been already published about that purpose, some existing algorithms have been selected and brought together to achieve a robust color segmentation, as fast as possible. The foreseen application is a good training ground to evaluate these algorithms since main difficulties came from the complexity of the scene, the moving background due to breathing motion, the high surface reflectance, the non-uniform and time-varying lighting conditions. Nevertheless, to achieve the image segmentation suitable for robot control, we propose a new approach, without markers, based on a recursive thresholding of the histogram of a new purity color attribute and region growing. The main contribution of this work is threefold and consists in: the definition of a new color purity component, a selection of reliable, fast and robust existing video processings for the above-mentioned application areas, improving some existing video processings to enhance color properties either to homogenize regions and to emphasize the saturation feature of chromatic pixels. The usefulness of the proposed set of sequential processings has been successfully validated with image sequences of an endoscope to efficiently extracting boundaries of a cylindrical needle-holder with a sampling rate of 5 Hz.