Inference process of programmed attributed regular grammars for character recognition

Mihail Prundaru; Ioana Prundaru

doi:10.1117/12.410848

21 December 2000 Inference process of programmed attributed regular grammars for character recognition

Mihail Prundaru, Ioana Prundaru

Proceedings Volume 4307, Document Recognition and Retrieval VIII; (2000) https://doi.org/10.1117/12.410848
Event: Photonics West 2001 - Electronic Imaging, 2001, San Jose, CA, United States

Abstract

The paper presents the grammar inference engine of a pattern recognition system for character recognition. The input characters are identified, thinned to a one pixel width pattern and a feature-based description is provided. Using the syntactic recognition paradigm, the features are the set of terminals (or terminal symbols) for the application. The feature-based description includes a set of three attributes (i.e. A, B, C) for each feature. The combined feature and attribute description for each input pattern preserves in a more accurate way the structure of the original pattern. The grammar inference engine uses the feature-based description of each input pattern from the training set to build a grammar for each class of patterns. For each input pattern from the training set, the productions (rewriting rules) are derived together with all the necessary elements such as: the nonterminals, branch and testing conditions. Since the grammars are regular, the process of deriving the production rules is simple. All the productions are collected together providing the tags to be consecutive, without gaps. The size of the class grammars is reduced at an acceptable level for further processing using a set of Evans heuristic rules. These algorithms identifies the redundant productions, eliminating those productions and the correspondent nonterminal symbols. The stop criteria for the Evans thinning algorithm makes sure that no further reductions are possible. The last step of the grammar inference process enables the grammar to identify class members which were not in the training set: a cycling production rule. The above built grammars are used by the syntactic (character) classifier to identify the input patterns as being members of a-priori known classes.

Citation Download Citation

Mihail Prundaru and Ioana Prundaru "Inference process of programmed attributed regular grammars for character recognition", Proc. SPIE 4307, Document Recognition and Retrieval VIII, (21 December 2000); https://doi.org/10.1117/12.410848

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available

Members: $17.00

Non-members: $21.00 ADD TO CART

PROCEEDINGS
7 PAGES

DOWNLOAD PAPER SAVE TO MY LIBRARY

GET CITATION

RIGHTS & PERMISSIONS

Get copyright permission Get copyright permission on Copyright Marketplace

KEYWORDS

Optical character recognition

Pattern recognition

Inspection

Detection and tracking algorithms

Neodymium

Analog electronics

Argon

Show All Keywords

Keywords/Phrases

Search In:

Publication Years