58 research outputs found

    2D Grey-level Skeleton Computation: A Discrete 3D Approach

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    A discrete 3D binary approach to compute the skeleton in 2D grey-level images is presented. The 2D grey-level input image is converted to a 3D binary image and the top surface of the foreground is identified. This discrete surface then undergoes skeletonization. The obtained 3D curve skeleton is pruned, before being projected back to a 2D grey-level image. This is suitably post-processed, since the projection may cause spurious loops and thickening. This algorithm can find applications in optical character recognition and document analysis or in other situations where shape analysis by skeletons is desired. An important property of the suggested method is that no hard segmentation into foreground and background is needed prior to the skeletonization

    Proceedings of the 9th International Conference on Pattern Recognition Applications and Methods 2020

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    This book includes the papers accepted for presentation at the 9th International Conference on Pattern Recognition Applications and Methods (ICPRAM 2020), Valletta, Malta, February 22-24, 2020. The conference is sponsored by the Institute for Systems and Technologies of Information, Control and Communication (INSTICC) and is endorsed by the International Association for Pattern Recognition (IAPR). ICPRAM 2020 is organized “in cooperation” with the ACM Special Interest Group on Artificial Intelligence (ACM SIGAI), the European Association for Signal Processing (EURASIP), the Italian Association for Artificial Intelligence (AI*IA) and the Associação Portuguesa de Reconhecimento de Padrões (APRP). ICPRAM is an annual conference and since its first edition, held in 2012, has been a major point of contact between researchers, engineers and practitioners on the areas of Pattern Recognition and Machine Learning, both from theoretical and application perspectives

    Editorial

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