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Automatic Recognition of Handwritten Bangla Courtesy Amount on Bank Checks


Shahin Shah, S. M. Anamul Haque, Rafiqul Islam, Abbas Ali, Mohammad Shabbir Hasan


Vol. 10  No. 12  pp. 154-163


In spite of rapid evolution of electronic techniques, a number of large-scale applications continue to rely on the use of paper as the dominant medium. This is especially true for processing of bank checks. This paper presents a recognition system of handwritten Bangla courtesy amount on a bank check. The system uses the scanned image of a blank check to read the amount written by the user. There are four main stages in the systems that focus on: the detection of courtesy amount block within the image; the segmentation of string into characters; the recognition of isolated characters; and the post-processing process that ensures correct recognition. The detection of courtesy amounts is performed using image-cropping methods. The segmentation of the courtesy amount is the most difficult part of the process because of the largely unconstrained nature of handwritten amounts on checks. The segmentation module has been implemented as a recursive process that interacts with the recognition module. The recognition of the isolated characters is based on neural a network that has been demonstrated to be very accurate and computationally efficient. A Backpropagation learning algorithm is used to train up the network. The performance of the system is tested in different sorts of numeral and the experimental result shows satisfactory performance.


Bank Check, Courtesy Amount, Segmentation, Neural Network Recognition