A high performance banknote recognition system based on a one-dimensional visible light line sensor

Young Ho Park, Seung Yong Kwon, Tuyen Danh Pham, Kang Ryoung Park, Dae Sik Jeong, Sungsoo Yoon

Research output: Contribution to journalArticlepeer-review

16 Scopus citations

Abstract

An algorithm for recognizing banknotes is required in many fields, such as banknote-counting machines and automatic teller machines (ATM). Due to the size and cost limitations of banknote-counting machines and ATMs, the banknote image is usually captured by a one-dimensional (line) sensor instead of a conventional two-dimensional (area) sensor. Because the banknote image is captured by the line sensor while it is moved at fast speed through the rollers inside the banknote-counting machine or ATM, misalignment, geometric distortion, and non-uniform illumination of the captured images frequently occur, which degrades the banknote recognition accuracy. To overcome these problems, we propose a new method for recognizing banknotes. The experimental results using two-fold cross-validation for 61,240 United States dollar (USD) images show that the pre-classification error rate is 0%, and the average error rate for the final recognition of the USD banknotes is 0.114%.

Original languageEnglish
Pages (from-to)14093-14115
Number of pages23
JournalSensors
Volume15
Issue number6
DOIs
StatePublished - 15 Jun 2015

Keywords

  • Banknote recognition
  • One-dimensional (line) sensor
  • Pre-classification
  • USD banknote

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