{'fraction_non_alphanumeric': 0.01752021563342318, 'fraction_numerical': 0.0, 'mean_word_length': 5.140495867768595, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Artifacts Removal in Melanoma Using Various Preprocessing Filters

Preprocessing plays an important role for artifacts removal and quality improvement. In this paper, noise and hair removal techniques for melanoma in dermoscopic images is proposed. Here the performance of four filters for noise removal namely Wiener, Mean, Median, and Gaussian Filters are studied. Of these the performance of Gaussian filter is proved to be best. In addition Morphological Filter is used for hair removal. The noise and hair removal filtering processes help to enhance the quality of the image and thus aid to improve the segmentation results. The performance of the preprocessing filters is compared using quantifying parameters like MSE, PSNR, and SSIM. 