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</script>Skin cancer exists in different forms such as: Melanoma, Basal and Squamous Cell Carcinoma, among which Melanoma is the most dangerous and unpredictable skin cancer. In this paper, we implement an image processing technique for the detection of Melanoma skin cancer, in which the input to the system is the skin lesion image. This image proceeds with the image preprocessing methods such as conversion of (Red, Green, Blue)RGB image to gray scale image, noise removal, hair removal and so on. Moreover thresholding is used to segment the images followed by feature extraction that includes parameters such as: Asymmetry, Border irregularity, Color and Diameter (ABCD). Finally, the total Dermoscopic score (TDS) is calculated and decision is to be taken whether the cancer is Melanoma or not
| citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 2 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
