OFF-LINE UNCONSTRAINED HANDWRITTEN WORD RECOGNITION-Reference-Cited by-同舟云学术

OFF-LINE UNCONSTRAINED HANDWRITTEN WORD RECOGNITION

Published:2000-05 Issue:03 Volume:14 Page:259-280
ISSN:0218-0014
Container-title:International Journal of Pattern Recognition and Artificial Intelligence
language:en
Short-container-title:Int. J. Patt. Recogn. Artif. Intell.

Author:

CAI JINHAI¹,LIU ZHI-QIANG¹

Affiliation:

1. Computer Vision and Machine Intelligence Lab, Department of Computer Science, University of Melbourne, Parkville, VIC 3052, Australia

Abstract

In this paper, we describe our system for writer independent, off-line unconstrained handwritten word recognition. We have developed a new method to automatically determine the parameters of Gabor filters to extract features from slant and tilt corrected images. An algorithm is also developed to translate 2D images to 1D domain. Finally, we propose a modified dynamic programming method with fuzzy theory to recognize words. Our initial experiments have shown promising results.

Publisher

World Scientific Pub Co Pte Lt

Subject

Artificial Intelligence,Computer Vision and Pattern Recognition,Software

Link

https://www.worldscientific.com/doi/pdf/10.1142/S0218001400000180

Reference25 articles.

1. A fuzzy graph theoretic approach to recognize the totally unconstrained handwritten numerals

2. Off-line cursive script word recognition

3. Off-line cursive handwriting recognition using hidden markov models

4. A structural and relational approach to handwritten word recognition

5. Variable duration hidden Markov model and morphological segmentation for handwritten word recognition

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