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Robust text segmentation using graph cut
2015 13th International Conference on Document Analysis and Recognition (ICDAR)
Text segmentation provides important clues for the accurate identification of character locations and the analysis of character properties such as shape estimation and texture synthesis. In this paper, we propose a robust text segmentation method that employs Markov Random Field (MRF) and use graph cut algorithms to solve the energy minimization problem. To effectively select accurate seeds to boost the text segmentation performance, stroke feature transform is adopted to robustly identify textdoi:10.1109/icdar.2015.7333778 dblp:conf/icdar/TianLST15 fatcat:adkgs2mwlveclps32i7wujfqbu