A novel model-based approach for 3D footwear outsole feature extraction (original) (raw)

International Symposium on Image and Signal Processing and Analysis, 2009

Abstract

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.

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