Features for melanoma lesions characterization in computer vision systems

Computer vision systems are increasingly used for the early detection of skin diseases, such as malignant melanoma. The various proposals of computer vision systems are characterized by some fundamental common phases: image acquisition, pre-processing, segmentation, features extraction and selection and finally classification. In most of the related papers dealing with this topic, many features are extracted in order to feed classifiers from the simplest to the most sophisticated. Features are typically extracted using digital image processing methods (i.e., segmentation, edge detection and color and structure processing), and an open discussion about the meaning of these features and the objective ways of measuring them is ongoing. Therefore, the need to investigate this topic in order to find a guideline to support new researchers on these issues arises. The present work is a not exhaustive review of the most frequently used features in the elaboration of computer vision systems. The shortcomings in some of the existing studies are highlighted and suggestions for future research are provided.