Recognition of handprinted numerals in VISA® card application forms

Jung Hsien Chiang, Paul D. Gader

Research output: Contribution to journalArticlepeer-review

15 Citations (Scopus)

Abstract

An optical character recognition (OCR) frame-work 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 net-work. 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.

Original languageEnglish
Pages (from-to)144-149
Number of pages6
JournalMachine Vision and Applications
Volume10
Issue number3
DOIs
Publication statusPublished - 1997 Jan 1

All Science Journal Classification (ASJC) codes

  • Software
  • Hardware and Architecture
  • Computer Vision and Pattern Recognition
  • Computer Science Applications

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