Title :
New paradigm for segmentation and recognition of handwritten numeral string
Author :
Yoon, Sungsoo ; Kim, Gyeonghwan ; Choi, Yeongwoo ; Lee, Yillbyung
Author_Institution :
Dept. of Comput. Sci., Yonsei Univ., Seoul, South Korea
fDate :
6/23/1905 12:00:00 AM
Abstract :
String recognition is rather paradoxical problem because it requires the segmentation of the string into understandable units, but proper segmentation needs a-priori knowledge of the units and this implies a recognition capability. To solve this dilemma therefore, both a-priori knowledge of meaningful units and a segmentation method have to be used together, and they should dynamically interact with each other. In other words, the results of segmentation are used as fundamental information to suppose what is most likely to be, and then its a-priori knowledge is used to help the segmentation. This model makes explicit segmentation unnecessary because it does not speculate on possible break positions. It is also possible to recognize a digit even if it contains strokes that do not belong to to it. Using this paradigm for 100 handwritten numeral strings belonging to the NIST database has resulted in 95% recognition
Keywords :
handwritten character recognition; image segmentation; optical character recognition; NIST database; a-priori knowledge; break positions; digit recognition; dynamically interacting methods; handwritten numeral string recognition; string segmentation; understandable units; Character recognition; Computational complexity; Computer science; Databases; Handwriting recognition; Hidden Markov models; Image segmentation; Knowledge engineering; NIST; Pattern recognition;
Conference_Titel :
Document Analysis and Recognition, 2001. Proceedings. Sixth International Conference on
Conference_Location :
Seattle, WA
Print_ISBN :
0-7695-1263-1
DOI :
10.1109/ICDAR.2001.953784