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To enhance the performance of shoeprint recognition systems, an approach capable of extracting the information-rich 3D outsole patterns is regarded as a promising one. In this paper, initial work on this approach is reported. In this method, 3D outsole models captured using a 3D scanner are sliced in stripes. Stripes are subsequently fitted to parabolas to discover the outsole profiles. Convex/Concave features are hence extracted from each stripe and further fitted by a parametric model to estimate the feature centre position, and the vertical and the horizontal scales. Finally, by grouping estimated features together, a Fuzzy C-Means based method for extracting Printable 3D Features from Convex-Pattern-Dominant Outsoles (Convex-PDOs) is proposed. Promising experimental results show the feasibility of our model-based method for further 3D feature extraction.