Applying the OCRopus OCR System to Scholarly Sanskrit Literature
Sanskrit Computational Linguistics
Recent progress on the OCRopus OCR system
Proceedings of the International Workshop on Multilingual OCR
Stroke number and order free handwriting recognition for Nepali
PRICAI'06 Proceedings of the 9th Pacific Rim international conference on Artificial intelligence
Unsupervised font reconstruction based on token co-occurrence
Proceedings of the 10th ACM symposium on Document engineering
Evaluating glyph binarizations based on their properties
Proceedings of the 2013 ACM symposium on Document engineering
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Abstract: Segmentation of handwritten input into individual characters is a crucial step in many connected handwriting recognition systems. This paper describes a segmentation algorithm for letters in Roman alphabets, curved pre-stroke cut (CPSC) segmentation. The CPSC algorithm evaluates large set of curved cuts through the image of the input string using dynamic programming and selects a small "optimal" subset of cuts for segmentation. It usually generates pixel accurate segmentations, indistinguishable from characters written in isolation. At four times oversegmentation, segmentation points are missed with an undetectable frequency on real-world databases. The CPSC algorithm has been used as part of a high-performance handwriting recognition system.