Building a new generation of handwriting recognition systems
Pattern Recognition Letters - Postal processing and character recognition
N-Tuple Features for OCR Revisited
IEEE Transactions on Pattern Analysis and Machine Intelligence
Digital Image Processing
Touching numeral segmentation using water reservoir concept
Pattern Recognition Letters
ICDAR '97 Proceedings of the 4th International Conference on Document Analysis and Recognition
Handwritten Character Recognition Based on Structural Characteristics
ICPR '02 Proceedings of the 16 th International Conference on Pattern Recognition (ICPR'02) Volume 3 - Volume 3
A new generation of textual corpora: mining corpora from very large collections
Proceedings of the 7th ACM/IEEE-CS joint conference on Digital libraries
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Recognition of handwritten manuscripts is essential for efficient content exploitation of the valuable Old Greek historical collections. In this paper, we focus on the problem of recognizing Old Greek handwritten manuscripts and propose a novel recognition technique that can be applied to a large number of important historical manuscript collections which are written in lower case letters and originate from St. Catherine's Mount Sinai Monastery. Based on an open and closed cavity character representation, we propose a novel, segmentation-free, fast and efficient technique for the detection and recognition of characters and character ligatures. First, we detect open and closed cavities that exist in the skeletonized character body. Then, the recognition of a specific character or character ligature is based on the protrusible segments that appear in the topological description of the character skeletons. Experimental results prove the efficiency of the proposed approach.