DocumentCode
1415572
Title
A statistical, nonparametric methodology for document degradation model validation
Author
Kanungo, Tapas ; Haralick, Robert M. ; Baird, Henry S. ; Stuezle, Werner ; Madigan, David
Author_Institution
Center for Autom. Res., Maryland Univ., College Park, MD, USA
Volume
22
Issue
11
fYear
2000
fDate
11/1/2000 12:00:00 AM
Firstpage
1209
Lastpage
1223
Abstract
Printing, photocopying, and scanning processes degrade the image quality of a document. Statistical models of these degradation processes are crucial for document image understanding research. In this paper, we present a statistical methodology that can be used to validate local degradation models. This method is based on a nonparametric, two-sample permutation test. Another standard statistical device, the power function, is then used to choose between algorithm variables such as distance functions. Since the validation and the power function procedures are independent of the model, they can be used to validate any other degradation model. A method for comparing any two models is also described. It uses p-values associated with the estimated models to select the model that is closer to the real world.
Keywords
document image processing; optical character recognition; parameter estimation; statistical analysis; document degradation model; model validation; nonparametric statistical test; optical character recognition; parameter estimation; simulation models; statistical models; two-sample permutation test; Algorithm design and analysis; Control system synthesis; Degradation; Electric breakdown; Image quality; Optical character recognition software; Optimal control; Predictive models; System performance; Testing;
fLanguage
English
Journal_Title
Pattern Analysis and Machine Intelligence, IEEE Transactions on
Publisher
ieee
ISSN
0162-8828
Type
jour
DOI
10.1109/34.888707
Filename
888707
Link To Document