TITLE:
Fuzzy C Mean Thresholding based Level Set for Automated Segmentation of Skin Lesions
AUTHORS:
Ammara Masood, Adel Ali Al-Jumaily
KEYWORDS:
Skin Cancer; Segmentation; Diagnosis; Fuzzy; Thresholding; Level Sets
JOURNAL NAME:
Journal of Signal and Information Processing,
Vol.4 No.3B,
October
16,
2013
ABSTRACT:
Accurate segmentation is an important
and challenging task in any computer vision system. It also plays a vital role
in computerized analysis of skin lesion images. This paper presents a new
segmentation method that combines the advan-tages of fuzzy C mean algorithm,
thresholding and level set method. 3-class Fuzzy C mean thresholding is applied
to initialize level set automatically and also for estimating controlling
parameters for level set evolution. Parameters for performance evaluation are
presented and segmentation results are compared with some other
state-of-the-art segmentation methods. Increased true detection rate and reduced false positive
and false negative errors confirm the effectiveness of proposed method for skin
cancer detection.