An efficient block-based algorithm for hair removal in dermoscopic images
Автор: Zaqout Ihab Salah
Журнал: Компьютерная оптика @computer-optics
Рубрика: Image processing, pattern recognition
Статья в выпуске: 4 т.41, 2017 года.
Бесплатный доступ
Hair occlusion in dermoscopy images affects the diagnostic operation of the skin lesion. Segmentation and classification of skin lesions are two major steps of the diagnostic operation required by dermatologists. We propose a new algorithm for hair removal in dermoscopy images that includes two main stages: hair detection and inpainting. In hair detection, a morphological bottom-hat operation is implemented on Y-channel image of YIQ color space followed by a binarization operation. In inpainting, the repaired Y-channel is partitioned into 256 non-overlapped blocks and for each block, white pixels are replaced by locating the highest peak, using a histogram function and a morphological close operation. The proposed algorithm reports a true positive rate (sensitivity) of 97.36 %, a false positive rate (fall-out) of 4.25 %, and a true negative rate (specificity) of 95.75 %. The diagnostic accuracy achieved is recorded at a high level of 95.78 %.
Dermoscopy image, melanoma, hair detection, hair removal, inpainting, skin lesion
Короткий адрес: https://sciup.org/140228638
IDR: 140228638 | DOI: 10.18287/2412-6179-2017-41-4-521-527.
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