In recent days, skin cancer is seen as one of the most Hazardous form of the Cancers found in Humans. Skin cancer is found in various types such as Melanoma, Basal and Squamous cell Carcinoma among which Melanoma is the most unpredictable. The detection of Melanoma cancer in early stage can be helpful to cure it. Computer vision can play important role in Medical Image Diagnosis and it has been proved by many existing systems. In this paper, we present a computer aided method for the detection of Melanoma Skin Cancer using Image Processing tools. The input to the system is the skin lesion image and then by applying novel image processing techniques, it analyses it to conclude about the presence of skin cancer. The Lesion Image analysis tools checks for the various Melanoma parameters Like Asymmetry, Border, Colour, Diameter,(ABCD) etc. by texture, size and shape analysis for image segmentation and feature stages. The extracted feature parameters are used to classify the image as Normal skin and Melanoma cancer lesion.

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Normal moles are mostly small brown in color that are spots or growths on the skin that is by birth or emerge in the first few decades of life in almost everyone. Skin cancer most often appears as moles. Seldom people are aware about the skin cancer. If detected at early stages then it can be cured. We propose an improved design of Gabor filter which is combined with Vedic algorithm (Urdhva Triyagbhyam) to give faster convolution result. The exertion has proved the efficiency of Urdhva Triyagbhyam which is the Vedic method of multiplication that enables parallel generation of intermediary products that eliminates unwanted multiplication steps with zeros and scaled to higher bit. In this paper we employ the filter design appropriate for detecting the early stages of skin cancer using textural properties of skin.