ABSTRACT
Australia is one of many countries in which skin cancer is simply “wide spread” in comparison to other types of cancer [1] [2]. Researchers have found that Australian melanoma rates are the highest globally at almost four times the rates seen in Canada, the United Kingdom and the United States[3]. Skin cancer costs the health system around $300 million Australian dollars annually, the highest cost of all cancers. Melanoma has near 95% cure rate if detected and treated in its early stages [4]. This study proposes an automated system for discrimination between melanocytic nevi and malignant melanoma. The general approach of developing a Computer Aided Diagnostic system for the diagnosis of skin cancer is to find the location of a lesion and also to determine an estimate of the probability of a disease. As mentioned in the literature the digital images are often corrupted during acquisition and transmission [5]. Filters are then very important as pre-processing tools.
