Abstract
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 %.
Highlights
Melanoma, otherwise called malignant melanoma, is a kind of cancer that is created from the pigment-containing cells known as melanocytes
The implementation of the hair removal process is divided into two main stages: hair detection and inpainting
A morphological bottom-hat operation is implemented on Y-channel image of the YIQ color space followed by a binarization operation
Summary
Otherwise called malignant melanoma, is a kind of cancer that is created from the pigment-containing cells known as melanocytes. It is created in the cells that give the skin its color (melanocytes) and has a high inclination to spread to different parts of the body. On the off-chance that melanoma is perceived and treated early, it is quite often repairable; in the event that it is not, the disease can progress and spread to different parts of the body, where it turns out to be difficult to treat and can be lethal. While it is not the most well-known of the skin cancers, it causes the most deaths
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