High-performance OCR preclassification trees

Henry S. Baird; C. L. Mallows

doi:10.1117/12.205840

30 March 1995 High-performance OCR preclassification trees

Henry S. Baird, C. L. Mallows

Proceedings Volume 2422, Document Recognition II; (1995) https://doi.org/10.1117/12.205840
Event: IS&T/SPIE's Symposium on Electronic Imaging: Science and Technology, 1995, San Jose, CA, United States

Abstract

We present an automatic method for constructing high-performance preclassification decision trees for OCR. Good preclassifiers prune the set of alternative classes to many fewer without erroneously pruning the correct class. We build the decision tree using greedy entropy minimization, using pseudo-randomly generated training samples derived from a model of imaging defects, and then `populate' the tree with many more samples to drive down the error rate. In [BM94] we presented a statistically rigorous stopping rule for population that enforces a user-specified upper bound on error: this works in practice, but is too conservative, driving the error far below the bound. Here, we describe a refinement that achieves the user- specified accuracy more closely and thus improves the pruning rate of the resulting tree. The method exploits the structure of the tree: the essential technical device is a leaf-selection rule based on Good's Theorem [Good53]. We illustrate its effectiveness through experiments on a pan-European polyfont classifier.

Citation Download Citation

Henry S. Baird and C. L. Mallows "High-performance OCR preclassification trees", Proc. SPIE 2422, Document Recognition II, (30 March 1995); https://doi.org/10.1117/12.205840

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

Error analysis

Optical character recognition

Statistical modeling

Binary data

Computing systems

Data modeling

Image classification

Show All Keywords

Keywords/Phrases

Search In:

Publication Years