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Pigment network is considered a key differential structure by dermatologists. Recently, different approaches have been proposed for the detection and characterization of this structure. This paper proposes an improved system for automatic detection of pigment network regions. The system starts by detecting the presence of pigment network using a bank of directional filters and a connected component analysis. After, a set of features, which characterize the pigment network's lines and the background, is extracted and used to validate the detected regions with AdaBoost. Finally, each lesion is classified regarding the presence or absence of pigment network The algorithm was tested in a dataset of dermoscopy images from Hospital Pedro Hispano (Matosinhos) achieving a SE = 78% and a SP = 77% for five fold cross validation.