US 8,150,160 B2Granted

Automatic Arabic text image optical character recognition method

AssigneeKing Fahd University of Petroleum and Minerals

InventorsHusni A. Al-Muhtaseb, Sabri A. Mahmoud, Rami Qahwaji

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Abstract

The automatic Arabic text image optical character recognition method includes training a text recognition system using Arabic printed text, using the produced models for classification of newly unseen Arabic scanned text, and generating the corresponding textual information. Scanned images of Arabic text and copies of minimal Arabic text are used in the training sessions. Each page is segmented into lines. Features of each line are extracted and input to Hidden Markov Model (HMM). All training data training features are used. HMM runs training algorithms to produce codebook and language models. In the classification stage new Arabic text is input in scanned form. Line segmentation where lines are extracted is passed through. In the feature stage, line features are extracted and input to the classification stage. In the classification stage the corresponding Arabic text is generated.

Claims16

Dependent claims

A computer-implemented automatic Arabic text image optical character recognition method, comprising the steps of:

accepting as input an optical image of Arabic text and a predetermined selection of minimal Arabic text, the selection of minimal Arabic text representing substantially all Arabic letter shape occurrences likely to be input as text for character recognition;
arranging all of the input Arabic text into a plurality of text image rows;
segmenting each of the Arabic text input rows into a hierarchical stack of six segments vertically;
performing feature extraction on the six segments of Arabic text for at least one of the input rows;
inputting results from the feature extraction step into a Hidden Markov Model (HMM);
storing results from the HMM to an HMM models database and to a language model database;
performing a statistical syntactical analysis on the at least one input row of Arabic text;
storing results of the statistical syntactical analysis to the language model database;
selecting an optimized HMM from the HMM models database based on the statistical results stored in the language model database;
inputting additional Arabic text;
and
performing text recognition on the additional Arabic text utilizing the optimized HMM.

9 more elements

Dependencies are inferred from the claim text.