Filtering segmentation cuts for digit string recognition |
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Authors: | E Vellasques LS Oliveira AS Britto AL Koerich R Sabourin |
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Affiliation: | 1. Transplant Immunology Group, Academic Department of Haematology & Oncology, University of Leeds, UK;2. Department of Haematology, Calderdale and Huddersfield NHS Trust, UK;3. Academic Department of Haematology & Oncology, University of Leeds, UK;4. Department of Haematology, St James''s Institute of Oncology, Leeds Teaching Hospitals NHS Trust, UK;2. U‐Center, Epen, The Netherlands;3. Ghent University, Ghent, Belgium;4. Maastricht University, Maastricht, The Netherlands;5. Catharina Hospital, Eindhoven, The Netherlands |
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Abstract: | In this paper we propose a method to evaluate segmentation cuts for handwritten touching digits. The idea of this method is to work as a filter in segmentation-based recognition system. This kind of system usually rely on over-segmentation methods, where several segmentation hypotheses are created for each touching group of digits and then assessed by a general-purpose classifier. The novelty of the proposed methodology lies in the fact that unnecessary segmentation cuts can be identified without any attempt of classification by a general-purpose classifier, reducing the number of paths in a segmentation graph, what can consequently lead to a reduction in computational cost. An cost-based approach using ROC (receiver operating characteristics) was deployed to optimize the filter. Experimental results show that the filter can eliminate up to 83% of the unnecessary segmentation hypothesis and increase the overall performance of the system. |
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