Title :
Connected character recognition with a neural network
Author :
Fukushima, Kunihiko
Author_Institution :
Dept. of Biophys. Eng., Osaka Univ., Japan
Abstract :
The selective attention model proposed by the author is a neural network model which has the ability to segment patterns, as well as the function of recognizing them. The principles of this selective attention model have been extended for the recognition and segmentation of connected characters. The topics discussed include the network architecture, pattern recognition, segmentation, repairing imperfect patterns, attention focusing, search control, attention switching, size and position information, and computer simulation. Improvement of the system using bend detectors is discussed
Keywords :
character recognition; digital simulation; image segmentation; neural nets; attention focusing; attention switching; bend detectors; computer simulation; connected character recognition; imperfect pattern repair; network architecture; neural network model; pattern recognition; pattern segmentation; position information; search control; selective attention model; size information; Character recognition; Deformable models; Feature extraction; Handwriting recognition; Image segmentation; Neural networks; Optical wavelength conversion; Pattern matching; Pattern recognition; Robustness;
Conference_Titel :
Document Analysis and Recognition, 1993., Proceedings of the Second International Conference on
Conference_Location :
Tsukuba Science City
Print_ISBN :
0-8186-4960-7
DOI :
10.1109/ICDAR.1993.395740