Journal article Open Access

GLOBAL CLASSIFICATION OF DERMATITIS DISEASE WITH K-MEANS CLUSTERING IMAGE SEGMENTATION METHODS

Prafulla N. Aerkewar1 & Dr. G. H. Agrawal2

The objective of this paper to presents a global technique for classification of  different  dermatitis disease lesions using the  process of k-Means clustering image segmentation method. The word global is used such that the all dermatitis disease having skin lesion on body are classified in to four category using k-means image segmentation and nntool of Matlab. Through the image segmentation technique and nntool can be  analyze and study the segmentation properties of skin lesions occurs in dermatitis disease. A skin lesion is a superficial growth or patch of the skin that does not resemble the area surrounding it. It have also been  proposed that which are suitable for the processing of various images for different types of patches for various skin diseases. The skin lesion in different dermatitis diseases are different in appearance and have different properties if they looks similar in some circumstances. The main objective to classify the lesions of different dermatitis diseases based on its twelve parameters like contrast, Energy, Homogeneity etc where it would be able to classify the similar patch in to different disease.  The focus is on Leprosy, Vitiligo, Psoriasis and other like birth mark or burn or boil skin patch which can be classify using  K-means clustering methods and nntool of Matlab..  This review the original ideas and concepts of  the above methods, because we believe this information collected and analyzed parameter are helpful to classify disease using Image Segmentation Technique

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