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Kuo et al., 1994 - Google Patents

Keyword spotting in poorly printed documents using pseudo 2-D hidden Markov models

Kuo et al., 1994

Document ID
13823449655788650096
Author
Kuo S
Agazzi O
Publication year
Publication venue
IEEE Transactions on pattern analysis and machine intelligence

External Links

Snippet

An algorithm for robust machine recognition of keywords embedded in a poorly printed document is presented. For each keyword, two statistical models, called pseudo 2-D hidden Markov models, are created for representing the actual keyword and all the other extraneous …
Continue reading at ieeexplore.ieee.org (other versions)

Classifications

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    • G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/62—Methods or arrangements for recognition using electronic means
    • G06K9/6201—Matching; Proximity measures
    • G06K9/6202—Comparing pixel values or logical combinations thereof, or feature values having positional relevance, e.g. template matching
    • G06K9/6203—Shifting or otherwise transforming the patterns to accommodate for positional errors
    • G—PHYSICS
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    • G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/62—Methods or arrangements for recognition using electronic means
    • G06K9/6267—Classification techniques
    • G06K9/6268—Classification techniques relating to the classification paradigm, e.g. parametric or non-parametric approaches
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    • G06K9/6217—Design or setup of recognition systems and techniques; Extraction of features in feature space; Clustering techniques; Blind source separation
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
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    • G06K9/4604—Detecting partial patterns, e.g. edges or contours, or configurations, e.g. loops, corners, strokes, intersections
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    • G—PHYSICS
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    • G06K9/72—Methods or arrangements for recognition using electronic means using context analysis based on the provisionally recognized identity of a number of successive patterns, e.g. a word
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    • G06K9/38—Quantising the analogue image signal, e.g. histogram thresholding for discrimination between background and foreground patterns
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    • G06K9/00852—Recognising whole cursive words
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