Multifractal-Based Features for Medical Images Classification

This paper presents a method to classify colored textural images of skin tissues. Since medical images have highly heterogeneity, the development of reliable skin-cancer detection process is difficult, and a mono fractal dimension is not sufficient to classify images of this nature. A multifractal-based feature vectors are suggested here as an alternative and more effective tool. At the same time multiple color channels are used to get more descriptive features. Two multifractal based set of features are suggested here. The first set measures the local roughness property, while the second set measure the local contrast property.A combination of all the extracted features from the three color models gives a highest classification accuracy with 99.4048% for training and 95.8333% for testing