NDLI: Machine vision for keyword spotting using pseudo 2D hidden Markov models

Content Provider	IEEE Xplore Digital Library
Author	Kuo, S.-s. Agazzi, O.E.
Copyright Year	1993
Description	Author affiliation: AT&T Bell Lab., Murray Hill, NJ, USA (Kuo, S.-s.; Agazzi, O.E.)
Abstract	An algorithm for robust machine recognition of keywords embedded in a poorly printed document is presented. For each keyword, two statistical models, called pseudo-2D hidden Markov models (P2-DHMMs), are created for representing the actual keyword and all the other extraneous words, respectively. Dynamic programming is then used for matching an unknown input word with the two models and making a maximum likelihood decision. Although the models are pseudo 2-D in the sense that they are not fully connected 2-D networks, they are shown to be general enough to characterize printed words efficiently. These models facilitate a nice 'elastic matching' property in both horizontal and vertical directions, which makes the recognizer not only independent of size and slant but also tolerant of highly deformed and noisy words. The system is evaluated on a synthetically created database which contains about 26000 words. A recognition accuracy of 99% is achieved when words in testing and training sets are in the same font size. An accuracy of 96% is achieved when they are in different sizes. In the latter case, the conventional 1-D HMM approach achieves only 70% accuracy rate.<>
Starting Page	81
Ending Page	84
File Size	449018
Page Count	4
File Format	PDF
ISBN	0780374029
ISSN	15206149
DOI	10.1109/ICASSP.1993.319752
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	1993-04-27
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Machine vision Hidden Markov models Optical distortion Nonlinear optics Optical filters Text recognition Signal processing algorithms Robustness Bayesian methods Impedance
Content Type	Text
Resource Type	Article

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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