Recognition of handprinted numerals in VISA® card application forms

An optical character recognition (OCR) framework is developed and applied to handprinted numeric fields recognition. The numeric fields were extracted from binary images of VISA® credit card application forms. The images include personal identity numbers and telephone numbers. The proposed OCR framework is a cascaded neural networks. The first stage is a self-organizing feature map algorithm. The second stage maps distance values into allograph membership values using a gradient descent learning algorithm. The third stage is a multi-layer feedforward network. In this paper, we present experimental results which demonstrate the ability to read handprinted numeric fields. Experiments were performed on a test data set from the CCL/ITRI database which consists of over 90,390 handwritten numeric digits.

Authors and Affiliations

1. Department of Information Management, Chaoyang Institute of Technology, Taiwan, R. O. C. , , , , , , TW

   Jung-Hsien Chiang

2. Department of Computer Engineering and Computer Science, University of Missouri, Columbia, MO 65211, USA , , , , , , US

   Paul D. Gader

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