A Lexicon Driven Method for Unconstrained Bangla

In this paper a lexicon driven segmentationrecognition scheme for unconstrained Bangla handwritten word recognition is proposed for Indian postal automation. In the proposed method, at first, binarization of the input document is done and slant correction of the individual words is performed. Next, using water reservoir concept words are pre-segmented into possible primitive components (characters or its parts). In order to merge these primitive components into characters and to find optimum character segmentation, dynamic programming (DP) is applied using total likelihood of characters as the objective function. To compute the likelihood of a character, modified quadratic discriminant function (MQDF) is used for the purpose. The features used in the MQDF are mainly based on the directional features of the contour points of the components. We tested our system on Bangla city-name images and at present an overall accuracy of 87.21% is obtained from the proposed system.

[1]  N. Otsu.  A threshold selection method from gray level histograms , 1979 .

[2]  Fumitaka Kimura,et al.  Modified Quadratic Discriminant Functions and the Application to Chinese Character Recognition , 1987, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[3]  Fumitaka Kimura,et al.  Improvements of a lexicon directed algorithm for recognition of unconstrained handwritten words , 1993, Proceedings of 2nd International Conference on Document Analysis and Recognition (ICDAR '93).

[4]  Jian Zhou,et al.  Off-Line Handwritten Word Recognition Using a Hidden Markov Model Type Stochastic Network , 1994, IEEE Trans. Pattern Anal. Mach. Intell..

[5]  Jung-Hsien Chiang,et al.  Handwritten word recognition with character and inter-character neural networks , 1997, IEEE Trans. Syst. Man Cybern. Part B.

[6]  Adnan Amin,et al.  Off-line Arabic character recognition: the state of the art , 1998, Pattern Recognit..

[7]  Sargur N. Srihari,et al.  On-Line and Off-Line Handwriting Recognition: A Comprehensive Survey , 2000, IEEE Trans. Pattern Anal. Mach. Intell..

[8]  John T. Favata.  Offline General Handwritten Word Recognition Using an Approximate BEAM Matching Algorithm , 2001, IEEE Trans. Pattern Anal. Mach. Intell..

[9]  Venu Govindaraju,et al.  The Role of Holistic Paradigms in Handwritten Word Recognition , 2001, IEEE Trans. Pattern Anal. Mach. Intell..

[10]  Cheng-Lin Liu,et al.  Lexicon-Driven Segmentation and Recognition of Handwritten Character Strings for Japanese Address Reading , 2002, IEEE Trans. Pattern Anal. Mach. Intell..

[11]  Umapada Pal,et al.  Multioriented and curved text lines extraction from Indian documents , 2004, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).

[12]  Xiaoqing Ding,et al.  Handwritten character recognition using gradient feature and quadratic classifier with multiple discrimination schemes , 2005, Eighth International Conference on Document Analysis and Recognition (ICDAR'05).

[13]  Bidyut Baran Chaudhuri,et al.  A system for Indian postal automation , 2005, Eighth International Conference on Document Analysis and Recognition (ICDAR'05).