By Topic

Morphological systems for character image processing and recognition

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

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

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