Assessment and Analysis on Color Image Classification Techniques of Dermatological Ulcers

With the implementation of color image processing methods, the image of dermatological ulcers are analyzed in order to detect the affected area of the skin. The detection of classification rate focus on the application of feature extraction method that segment, classify and analyze the tissue composition of skin lesions or ulcers. Indexing of skin ulcer images was performed based on the statistical texture features derived from the RGB color components. This literature assesses the high level methology for dermatological ulcer image classifier. The classifiers analyzed here are used for labeling the images by the dermatologist used in training and testing of the classifier. The classification performance rate, coverage area of the affected skin is analyzed based on the choice of different algorithms. Classifier uses the algorithm to perform attribute or feature selection that generates the candidate subsets of attributes and evaluate them by using the training and testing schemes, thus creating the computed values of corrected classified image rate up to 90% and assessed coverage area of affected skin up to 0.82. IndexTerms: Dermatological ulcers, Classification rate, Feature extraction, Classifiers. Texture features