NDLI: Performance prediction for handwritten word recognizers and its application to classifier combination

Content Provider	IEEE Xplore Digital Library
Author	Hanhong Xue Govindaraju, V.
Copyright Year	2002
Description	Author affiliation: CEDAR, State Univ. of New York, Buffalo, NY, USA (Hanhong Xue; Govindaraju, V.)
Abstract	This paper introduces a performance prediction model for handwritten word recognizers. This model considers the factors involved in word recognition, i.e., the recognizer, input images and lexicons, and presents a quantitative formula to associate performance with these factors. It produces a direct measure of recognition difficulty by the predicted performance which can be utilized to improve the combination of multiple recognizers. We support the accuracy of our model by extensive experiments conducted on five word recognizers and its applications to multiple classifier systems.
Starting Page	241
Ending Page	244
File Size	286799
Page Count	4
File Format	PDF
ISBN	076951695X
ISSN	10514651
DOI	10.1109/ICPR.2002.1047839
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2002-08-11
Publisher Place	Canada
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Handwriting recognition Image recognition Predictive models Image quality Pattern recognition Q measurement Venus Performance evaluation Image converters Image resolution
Content Type	Text
Resource Type	Article
Subject	Computer Vision and Pattern Recognition

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Performance prediction for handwritten word recognizers and its application to classifier combination