Skin lesion segmentation using Gray Level Co-occurance Matrix
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conference contribution
posted on 2024-06-04, 02:19 authored by M Hassan, M Hossny, S Nahavandi, A Yazdabadi© 2016 IEEE. Skin lesions screening is an effective method for early detection of melanoma. Mostly, melanoma appears as hyper-pigmented area relative to the surrounding skin. Lesion segmentation is an indispensable step for skin lesions analysis. Automated segmentation is used to assist the dermatologist to isolate the suspicious lesion from the surrounding background. Iterative Otsu's method is state-of-art segmentation technique and it has acceptable accuracy. However, iterative methods suffer same drawback, they are time consuming and no guarantee for convergence to the best solution before the maximum iterations limit reached. This paper presents a novel segmentation algorithm using GLCM (Gray Level Co-occurrence Matrix). Segmentation masks extracted by proposed method are compared to human-expert extracted ground truth. The proposed method consists of three major stages, preprocessing, segmentation, and post processing. The proposed method achieved a specificity rate of 98.62%, precision of 96.25% and sensitivity of 80.8%.
History
Pagination
820-825Location
Budapest, HungaryPublisher DOI
Start date
2016-10-09End date
2016-10-12ISBN-13
9781509018970Language
engPublication classification
E1 Full written paper - refereedCopyright notice
2016, IEEETitle of proceedings
SMC 2016 : IEEE International Conference on Systems, Man and CyberneticsEvent
Systems, Man and Cybernetics. International Conference (2016 : Budapest, Hungary)Publisher
IEEEPlace of publication
Piscataway, N.J.Usage metrics
Keywords
Licence
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