We present a method to detect and classify the dermoscopic structure pigment network which may indicate early melanoma in skin lesions. We locate the network as darker areas constituting a mesh, as well as lighter areas representing the 'holes' which the mesh surrounds. After identifying the lines and holes, 69 features inspired by the clinical definition are derived and used to classify the network into one of two classes: Typical or Atypical. We validate our method over a large, inclusive, real-world dataset consisting of 436 images and achieve an accuracy of 82% discriminating between three classes
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