J. Premaladha ¹, M. Lakshmi Priya ², S. Sujitha ², K. S. Ravichandran ¹

Affiliations
1 School of Computing, SASTRA University, Thanjavur - 613401, Tamil Nadu, IN
2 Department of ICT, School of Computing, SASTRA University, Thanjavur - 613401, Tamil Nadu, IN

Abstract

Melanoma is a deadly skin cancer which increases the death rate at a faster rate. In order to bring the death rate under control, melanoma should be detected at its earlier stage. To achieve this, researchers have introduced Computer aided diagnosis and adopted the same. In this technique, Segmentation is found to be one of the important steps. Many algorithms exist in practise for segmentation,where one of the important algorithms is Traditional Otsu Segmentation Algorithm. In this algorithm the major drawback is that the segmentation is improper in the presence of variable illumination. This paper proposes an algorithm "Normalised Otsu Segmentation" which overcomes the above mentioned drawback and results in an accurate segmentation. This algorithm first normalises the image to overcome variable illumination and then segments the image using Otsu algorithm. The accurate result given by this algorithm can be used in further steps to detect the lesion accurately which will provide a hand a for reducing the death rate.

Keywords

Illumination, Melanoma, Normalisation, Otsu’s Algorithm, Segmentation.

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J. Premaladha ¹, M. Lakshmi Priya ², S. Sujitha ², K. S. Ravichandran ¹

Affiliations
1 School of Computing, Sastra University, Thanjavur - 613401, Tamil Nadu, IN
2 Department of ICT, School of Computing, Sastra University, Thanjavur – 613401, Tamil Nadu, IN

Abstract

Image segmentation is an important process in Melanoma diagnosis. It divides the image into segments which provides a better path for extracting features and classifying them accordingly and so far many literatures have explained how the segmentation has been carried out for gray scale images. Though most algorithms have been written for gray scale images it is not necessary that we must stick on only to that instead we can also use color images directly for segmentation process. On doing so, variation in color can be used as an important feature for melanoma diagnosis. Color is a unique feature which can be used to provide a distinct differentiation between Melanoma and Benign. Hence on applying this color image segmentation, earlier detection can be done easily. This literature presents a survey on existing techniques for color image segmentation. Color images when segmented directly, yields better differentiation between the lesions.

Keywords

Benign, Color Image Segmentation, Gray Scale Images, Melanoma, Segmentation.

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