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|Title:||Image classification of skin moles & melanomas||Authors:||Luo, Ying||Keywords:||DRNTU::Engineering::Electrical and electronic engineering::Electronic systems::Signal processing||Issue Date:||2014||Abstract:||With the rapid development of image processing technologies, melanoma recognition system is gaining popularity both in research and medical purposes. The aim of this study is to investigate a good method to differentiate malignant melanomas from moles. In the recognition system, image segmentation should be done as a pre-processing step. Then morphological operation is applied to localize potential melanoma boundary regions. Next, discrimination features which provide good discrimination of malignant melanomas from moles are extracted. Finally, the selected features are applied to a neural network classifier to classify the skin lesion as melanoma or mole. With our approach, we obtained 82% correct classification rate in a dataset consisting of 100 images (50 moles and 50 melanomas) downloaded from DermQuest website.||URI:||http://hdl.handle.net/10356/65093||Fulltext Permission:||restricted||Fulltext Availability:||With Fulltext|
|Appears in Collections:||EEE Theses|
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