2017
DOI: 10.14445/23488549/ijece-v4i4p105
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Melanoma Skin Cancer Detection by Segmentation and Feature Extraction using combination of OTSU and STOLZ Algorithm Technique

Abstract: Skin cancer exists in different forms like Melanoma, Basal and Squamous cell Carcinoma among which Melanoma is the most dangerous and unpredictable. In this paper, we implement an image processing technique for the detection of Melanoma Skin Cancer using the software MATLAB which is easy for implementation as well as detection of Melanoma skin cancer. The input to the system is the skin lesion image. This image proceeds with the image pre-processing methods such as conversion of RGB image to Grayscale image, n… Show more

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Cited by 4 publications
(2 citation statements)
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“…Several researchers proposed an image analysis tools to check for the various melanoma parameters like asymmetry, border, color, diameter, in terms of 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 [16][17][18][19][20][21][22].…”
Section: Related Workmentioning
confidence: 99%
“…Several researchers proposed an image analysis tools to check for the various melanoma parameters like asymmetry, border, color, diameter, in terms of 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 [16][17][18][19][20][21][22].…”
Section: Related Workmentioning
confidence: 99%
“…One of the important fundamental functions of the automatic skin cancer surgery system is skin cancer boundary segmentation [3]; so many researchers are trying to focus on the research problem of segmentation of the skin cancer boundary to ensure the success of automatic surgery. In fact, the skin cancer boundary complicatedly consists of many tiny curves and angles with low contrast in some parts.…”
Section: Introductionmentioning
confidence: 99%