Melanoma recognition using extended set of descriptors and classifiers

作者：Kruk Michal^*; Swiderski Bartosz; Osowski Stanislaw; Kurek Jaroslaw; Slowinska Monika; Walecka Irena

来源：EURASIP Journal on Image and Video Processing, 2015, 2015(1): 43.

DOI：10.1186/s13640-015-0099-9

• Melanoma recognition
• Diagnostic features
• SVM
• Random forest

The paper presents a novel method of melanoma recognition on the basis of dermoscopic images. We use color images of skin lesions, advanced image processing, and different classifiers to distinguish melanoma from the other non-melanoma lesions. Different families of descriptors are used for generation of the image diagnostic features for final pattern recognition. To increase the efficiency of the system, we apply different selection procedures to find the best set of features and different solutions of classifier. The numerical results concerning the accuracy of the proposed recognition system have confirmed good accuracy of the proposed method and high sensitivity in melanoma recognition.

• 出版日期2015-12-14