Skin hair removal in dermoscopic images using soft color morphology
Artificial Intelligence in Medicine: 16th Conference on Artificial …, 2017•Springer
Dermoscopic images are useful tools towards the diagnosis and classification of skin
lesions. One of the first steps to automatically study them is the reduction of noise, which
includes bubbles caused by the immersion fluid and skin hair. In this work we provide an
effective hair removal algorithm for dermoscopic imagery employing soft color morphology
operators able to cope with color images. Our hair removal filter is essentially composed of a
morphological curvilinear object detector and a morphological-based inpainting algorithm …
lesions. One of the first steps to automatically study them is the reduction of noise, which
includes bubbles caused by the immersion fluid and skin hair. In this work we provide an
effective hair removal algorithm for dermoscopic imagery employing soft color morphology
operators able to cope with color images. Our hair removal filter is essentially composed of a
morphological curvilinear object detector and a morphological-based inpainting algorithm …
Abstract
Dermoscopic images are useful tools towards the diagnosis and classification of skin lesions. One of the first steps to automatically study them is the reduction of noise, which includes bubbles caused by the immersion fluid and skin hair. In this work we provide an effective hair removal algorithm for dermoscopic imagery employing soft color morphology operators able to cope with color images. Our hair removal filter is essentially composed of a morphological curvilinear object detector and a morphological-based inpainting algorithm. Our work is aimed at fulfilling two goals. First, to provide a successful yet efficient hair removal algorithm using the soft color morphology operators. Second, to compare it with other state-of-the-art algorithms and exhibit the good results of our approach, which maintains lesion’s features.
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