One of the greatest challenges in dermatology today is the early detection of melanoma since the success rates of curing this type of cancer are very high if detected during the early stages of its development. The main objective of the work presented in this paper is to create a prototype of a patient-oriented system for skin lesion analysis using a smartphone. This work aims at implementing a self-monitoring system that collects, processes, and stores information of skin lesions through the automatic extraction of specific visual features. The selection of the features was based on the ABCD rule, which considers 4 visual criteria considered highly relevant for the detection of malignant melanoma. The algorithms used to extract these features are briefly described and the results achieved using images taken from the smartphone camera are discussed.