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Optical Recognition of Credit Card Numbers  

Jung, Min Chul (Dept. of Computer System Engineering, Sangmyung University)
Publication Information
Journal of the Semiconductor & Display Technology / v.13, no.1, 2014 , pp. 57-62 More about this Journal
Abstract
This paper proposes a new optical recognition method of credit card numbers. Firstly, the proposed method segments numbers from the input image of a credit card. It uses the significant differences of standard deviations between the foreground numbers and the background. Secondly, the method extracts gradient features from the segmented numbers. The gradient features are defined as four directions of grayscale pixels for 16 regions of an input number. Finally, it utilizes an artificial neural network classifier that uses an error back-propagation algorithm. The proposed method is implemented using C language in an embedded Linux system for a high-speed real-time image processing. Experiments were conducted by using real credit card images. The results show that the proposed algorithm is quite successful for most credit cards. However, the method fails in some credit cards with strong background patterns.
Keywords
OCR; character segmentation; standard deviation; artificial neural networks; credit card recognition;
Citations & Related Records
Times Cited By KSCI : 1  (Citation Analysis)
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