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Morphological systems for character image processing and recognition

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2 Author(s)
P. -F. Yang ; Div. of Appl. Sci., Harvard Univ., Cambridge, MA, USA ; P. Maragos

Min/max signal operations, common in morphological image analysis were applied to both feature extraction and classification of character images. A system is proposed that computes an improved version of the morphological shape-size histogram. It reduces sensitivity to stroke thickness, size, and rotation. For pattern classification, the class of min-max classifier, which generalizes Boolean DNF functions for real-valued inputs, is introduced. A least mean square (LMS) algorithm was used for practical training of min-max classifiers. Experimental results show that min-max classifiers were able to achieve error rates comparable with those of neural networks trained using backpropagation. The main advantages of the min-max/LMS algorithm are its simplicity and faster speed of convergence.<>

Published in:

Acoustics, Speech, and Signal Processing, 1993. ICASSP-93., 1993 IEEE International Conference on  (Volume:5 )

Date of Conference:

27-30 April 1993