System, apparatus, and method for arabic handwriting recognition
AssigneeKing Fahd University of Petroleum and Minerals
InventorsSabri A. Mahmoud, Mohammed O. Assayony
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Abstract
A system, a non-transitory computer readable medium, and a method for Arabic handwriting recognition are provided. The method includes acquiring an input image representative of a handwritten Arabic text from a user, partitioning the input image into a plurality of regions, determining a bag of features representation for each region of the plurality of regions, modeling each region independently by multi stream discrete Hidden Markov Model (HMM), and identifying a text based on the HMM models.
Claims20
A method for Arabic handwriting recognition, the method comprising:
- acquiring, an input image representative of a handwritten Arabic text from a user;
- partitioning, using processing circuitry of a server, the input image into a plurality of regions;
- determining, using the processing circuitry, a bag of features representation for each region of the plurality of regions;
- modeling, using the processing circuitry, each region independently by multi stream discrete Hidden Markov Model (HMM);
- and
- identifying, using processing circuitry, a recognized text based on the HMM models.
A system for Arabic handwriting recognition, comprising:
- a client device;
- and
- a server including processing circuitry configured to
- acquire an input image representative of a handwritten Arabic text from the client device,
- partition the input image into a plurality of regions,
- determine a bag of features representation for each region of the plurality of regions,
- model each region independently by multi stream discrete Hidden Markov Model (HMM), and
- identify a text based on the HMM models.
A non-transitory computer readable medium storing computer-readable instructions therein which when executed by a computer cause the computer to perform a method for Arabic handwriting recognition, the method comprising:
- acquiring an input image representative of a handwritten Arabic text from a user;
- partitioning the input image into a plurality of regions;
- determining a bag of features representation for each region of the plurality of regions;
- modeling each region independently by multi stream discrete Hidden Markov Model (HMM);
- and
- identifying a text based on the HMM models.
Dependencies are inferred from the claim text.