Recognition of handprinted numerals in VISA(R) 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(R) 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.