• Vishwanath Burkpalli
• Shweta M Madiwal

Abstract: Skin cancer can be defined as skin growths with differing causes and various degrees of malignancy. Skin cancer can also be referred to as Skin Neoplasm’s. Skin cancer develops on skin and so can be seen. The main cause of Skin cancer all over the world is UV radiations coming from the sun and it is estimated that Americans are greatly affected by skin cancers than the Africans and Asians. This is due to the fair complexion of their skin and so less melanin. Whereas Africans and Asians due to the high melanin content in the skin is far resistant to skin cancer .It has been statistically proven that fairer skin toned people are much prone to tanning and so is prone to skin cancer. Untreated cancers can cause serious illness and death. In this work the presented a method called automatic segmentation of skin lesion in conventional macroscopic images. The main idea of this paper is segmenting the skin lesion from macroscopic images a novel approach region merging likelihood based on the statistics to determine the merger of region in a stochastic manner. The RBFN then processes the computed features and classifies the skin lesion either as a benign or a malignant. The paper discusses with intermediate results on sample skin images.

Index terms: Denoising, segmentation, radial basis function network

"Detection and classification of Skin cancer Using Color based Segmentation", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.5, Issue 7, page no.687-689, July-2018, Available :http://www.jetir.org/papers/JETIR1807702.pdf

"Detection and classification of Skin cancer Using Color based Segmentation", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.5, Issue 7, page no. pp687-689, July-2018, Available at : http://www.jetir.org/papers/JETIR1807702.pdf