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Comparison of Different Segmentation Algorithms for Dermoscopic Images


Affiliations
1 Department of Computer Science, Sadakathullah Appa College, India
2 Nandha Engineering College, India
     

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This paper compares different algorithms for the segmentation of skin lesions in dermoscopic images. The basic segmentation algorithms compared are Thresholding techniques (Global and Adaptive), Region based techniques (K-means, Fuzzy C means, Expectation Maximization and Statistical Region Merging), Contour models (Active Contour Model and Chan - Vese Model) and Spectral Clustering. Accuracy, sensitivity, specificity, Border error, Hammoude distance, Hausdorff distance, MSE, PSNR and elapsed time metrices were used to evaluate various segmentation techniques.

Keywords

Thresholding, Expectation Maximization, Contour Models, Dermoscopy, Spectral Clustering.
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  • Comparison of Different Segmentation Algorithms for Dermoscopic Images

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Authors

A. A. Haseena Thasneem
Department of Computer Science, Sadakathullah Appa College, India
R. Mehaboobathunnisa
Department of Computer Science, Sadakathullah Appa College, India
M. Mohammed Sathik
Department of Computer Science, Sadakathullah Appa College, India
S. Arumugam
Nandha Engineering College, India

Abstract


This paper compares different algorithms for the segmentation of skin lesions in dermoscopic images. The basic segmentation algorithms compared are Thresholding techniques (Global and Adaptive), Region based techniques (K-means, Fuzzy C means, Expectation Maximization and Statistical Region Merging), Contour models (Active Contour Model and Chan - Vese Model) and Spectral Clustering. Accuracy, sensitivity, specificity, Border error, Hammoude distance, Hausdorff distance, MSE, PSNR and elapsed time metrices were used to evaluate various segmentation techniques.

Keywords


Thresholding, Expectation Maximization, Contour Models, Dermoscopy, Spectral Clustering.