Skin Cancer Segmentation, Detection And Classification Using Hybrid Image Processing Technique

Neenu Paliwal

Now a days the application of image processing and segmentation plays an important role  in medical area. For cancer has found to be the most common and hazardous disease. . Skin cancer may be of different types like Melanoma, Basal and Squamous cell among which Melanoma is the most dangerous, uncertain and unpredictable. Detection of skin cancer in the earlier stage is important and can be helpful to cure it. For image segmentation and feature stages we can go through the Melanoma parameters Like Asymmetry, Border, Color, Diameter, (ABCD). With the help of texture, size and shape extracted feature parameters are used to classify the image as Melanoma cancer lesion or as a normal skin. . Computer vision can play important role in Medical area for Image Diagnosis. To deal with this trouble shoot there is  a requirement to develop e computer-aided diagnostic systems to facilitate the people for the early detection of the melanoma. The first step includes skin lesion segmentation. The next essential step is  to  extract the feature  and pattern analysis procedures to make a diagnosis of the affected area. This paper gives an idea to deal with   the segmentation, detection and classification of the skin cancer and the affected area using hybrid image processing techniques.