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This paper presents a method for vectorizing the graphical parts of paper-based line drawings. The method consists of separating the input binary image into layers of homogeneous thickness, skeletonizing each layer, segmenting the skeleton by a method based on random sampling, and simplifying the result. The segmentation method is robust with a best bound of 50 percent noise reached for indefinitely long primitives. Accurate estimation of the recognized vector's parameters is enabled by explicitly computing their feasibility domains. Theoretical performance analysis and expression of the complexity of the segmentation method are derived. Experimental results and comparisons with other vectorization systems are also provided.
Document analysis, graphics recognition and interpretation, vectorization, curve segmentation, performance evaluation, line drawings.

X. Hilaire and K. Tombre, "Robust and Accurate Vectorization of Line Drawings," in IEEE Transactions on Pattern Analysis & Machine Intelligence, vol. 28, no. , pp. 890-904, 2006.
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