DocumentCode :
3329500
Title :
Segmentation-free printed character recognition by relaxed nearest neighbor learning of windowed operator
Author :
Kim, Hae Yong
Author_Institution :
Dept. of Electron. Eng., Sao Paulo Univ., Brazil
fYear :
1999
fDate :
1999
Firstpage :
195
Lastpage :
204
Abstract :
Segmentation is considered by many researchers as the key technology for a reliable optical character recognition (OCR) system. To accomplish sound segmentation, many alternative techniques have been recently proposed. This paper presents a new technique to recognize characters without explicit segmentation. It is based on the automatic construction of a windowed operator by relaxed nearest neighbor learning. It has been implemented, tested and yielded excellent recognition accuracy and computational performance
Keywords :
optical character recognition; automatic windowed operator construction; computational performance; optical character recognition; recognition accuracy; relaxed nearest neighbor learning; segmentation-free printed character recognition; Character recognition; Error correction; Feedback loop; Image segmentation; Machine learning; Nearest neighbor searches; Optical character recognition software; Optical distortion; Optical feedback; Testing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Graphics and Image Processing, 1999. Proceedings. XII Brazilian Symposium on
Conference_Location :
Campinas
Print_ISBN :
0-7695-0481-7
Type :
conf
DOI :
10.1109/SIBGRA.1999.805725
Filename :
805725
Link To Document :
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