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Pattern recognition in macroscopic and dermoscopic images is a challenging task in skin lesion diagnosis. The search for better performing classification has been a relevant issue for pattern recognition in images. Hence, this work was particularly focused on skin lesion pattern recognition, especially in macroscopic and dermoscopic images. For the pattern recognition in macroscopic images, a computational approach was developed to detect skin lesion features according to the asymmetry, border, colour and texture properties, as well as to diagnose types of skin lesions, i.e., nevus, seborrheic keratosis and melanoma. In this approach, an anisotropic diffusion filter is applied to enhance the input image and an active contour model without edges is used in the segmentation of the enhanced image. Finally, a support vector machine is used to classify each feature property according to their clinical …