DocumentCode :
2043108
Title :
Detection of skin lesions by fuzzy entropy based texel identification
Author :
Susan, Seba ; Hanmandlu, M. ; Madasu, Vamsi K. ; Lovell, Brian C.
Author_Institution :
I.I.T. Delhi, Delhi, India
fYear :
2009
fDate :
16-18 Sept. 2009
Firstpage :
244
Lastpage :
249
Abstract :
This paper proposes automated detection of skin lesions by unsupervised feature based clustering based on a new fuzzy entropy function for characterizing texture. The parameterized entropy function is optimized using the Bacterial Foraging algorithm. The clustering of the entropy function of the image is done using the popular Fuzzy C-means algorithm (FCM). The experimental results obtained after the clustering process indicate a very good segregation of texture clusters with satisfactory visual results. The results also provide us with the normalized entropy values needed for texel identification.
Keywords :
entropy; fuzzy logic; image texture; medical image processing; object detection; pattern clustering; automated skin lesion detection; bacterial foraging algorithm; entropy function clustering; fuzzy C-means algorithm; fuzzy entropy based texel identification; fuzzy entropy function; image texture characterisation; parameterised entropy function; texture cluster segregation; unsupervised feature based clustering; Clustering algorithms; Entropy; Fuzzy sets; Image processing; Image segmentation; Lesions; Microorganisms; Polynomials; Skin; Uncertainty;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Image and Signal Processing and Analysis, 2009. ISPA 2009. Proceedings of 6th International Symposium on
Conference_Location :
Salzburg
ISSN :
1845-5921
Print_ISBN :
978-953-184-135-1
Type :
conf
DOI :
10.1109/ISPA.2009.5297716
Filename :
5297716
Link To Document :
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