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Krayem et al., 2013 - Google Patents

Holistic Arabic whole word recognition using HMM and block-based DCT

Krayem et al., 2013

Document ID
1237062565212382457
Author
Krayem A
Sherkat N
Evett L
Osman T
Publication year
Publication venue
2013 12th International Conference on Document Analysis and Recognition

External Links

Snippet

A review of the published research confirms that recognition of printed Arabic Word continues to present challenges. This is specially the case when segmentation is problematic. A word level recognition system is presented here that does not rely on any …
Continue reading at ieeexplore.ieee.org (other versions)

Classifications

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    • G06K9/62—Methods or arrangements for recognition using electronic means
    • G06K9/68—Methods or arrangements for recognition using electronic means using sequential comparisons of the image signals with a plurality of references in which the sequence of the image signals or the references is relevant, e.g. addressable memory
    • G06K9/6807—Dividing the references in groups prior to recognition, the recognition taking place in steps; Selecting relevant dictionaries
    • G06K9/6814—Dividing the references in groups prior to recognition, the recognition taking place in steps; Selecting relevant dictionaries according to the graphical properties
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    • G06K9/62—Methods or arrangements for recognition using electronic means
    • G06K9/6217—Design or setup of recognition systems and techniques; Extraction of features in feature space; Clustering techniques; Blind source separation
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    • G06K9/62—Methods or arrangements for recognition using electronic means
    • 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
    • G—PHYSICS
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    • G06K9/00852—Recognising whole cursive words
    • G—PHYSICS
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    • G06K9/03—Detection or correction of errors, e.g. by rescanning the pattern
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    • G10L15/00—Speech recognition
    • G10L15/02—Feature extraction for speech recognition; Selection of recognition unit

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