DocumentCode :
2215509
Title :
Characterization of skin lesions
Author :
Madhankumar, K. ; Kumar, P.
Author_Institution :
K.S. Rangasamy Coll. of Technol., Tiruchengode, India
fYear :
2012
fDate :
21-23 March 2012
Firstpage :
302
Lastpage :
306
Abstract :
Malignant melanoma is the deadliest form among all skin cancers. Fortunately, if detected early, even malignant melanoma may be treated successfully. In this paper, a new intelligent method of classifying benign and malignant melanoma lesions is used. As the first step of the image analysis, preprocessing techniques are used to remove noise and undesired structures from the images using filter such as median filtering. Segmentation is one of the important steps in cancer automatic detection, because it can greatly affect on the results of detection. In the second step, a simple thresholding method is used to segment and localize the lesion, a boundary tracing algorithm is also implemented to validate the segmentation. In the third step, the different features are extracted from a segmented image and classified by using Stolz algorithm.
Keywords :
cancer; feature extraction; image classification; image denoising; image segmentation; median filters; medical image processing; object detection; skin; Stolz algorithm; automatic cancer detection; boundary tracing algorithm; feature extraction; image analysis; image filtering; image segmentation; intelligent method; malignant melanoma; malignant melanoma lesion classification; median filtering; preprocessing techniques; simple thresholding method; skin cancers; skin lesion characterization; Cancer; Feature extraction; Image color analysis; Image segmentation; Lesions; Malignant tumors; Skin; Feature extraction; Thresholding method; automatic detection;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Pattern Recognition, Informatics and Medical Engineering (PRIME), 2012 International Conference on
Conference_Location :
Salem, Tamilnadu
Print_ISBN :
978-1-4673-1037-6
Type :
conf
DOI :
10.1109/ICPRIME.2012.6208362
Filename :
6208362
Link To Document :
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