METALLIC COIN ANALYZER SYSTEM FOR AUTOMATIC IDENTIFICATION AND CLASSIFICATION
Stefan Nicolae Tica (),
Costin-Anton Boiangiu () and
Ion Bucur ()
Additional contact information
Stefan Nicolae Tica: "Politehnica" University of Bucharest
Costin-Anton Boiangiu: "Politehnica" University of Bucharest
Ion Bucur: "Politehnica" University of Bucharest
Journal of Information Systems & Operations Management, 2015, vol. 9, issue 2, 291-308
Abstract:
In this paper, we would like to present and discuss a system that automatically classifies coins. This flexible system can identify coins having different features and being photographed in different light conditions. For this purpose, a set of strong techniques for thresholding, edge detection and frequency transform were used in order to generate a fingerprint as meaningful and as invariant as possible for every coin class. Usually, the capturing of digital images cannot be performed in best conditions and inconsistencies can arise due to various lighting conditions as well as the performance of the capturing device. This article is here to suggest a method to reduce problems generated by lighting, so that image characteristics are more accurate. The proposed solution improves an existing automatic coin classification algorithm by applying illumination correction before the actual classification.
Date: 2015
References: View complete reference list from CitEc
Citations:
Downloads: (external link)
http://www.rebe.rau.ro/RePEc/rau/jisomg/WI15/JISOM-WI15-A05.pdf (application/pdf)
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:rau:jisomg:v:10:y:2015:i:2:p:291-308
Access Statistics for this article
More articles in Journal of Information Systems & Operations Management from Romanian-American University Contact information at EDIRC.
Bibliographic data for series maintained by Alex Tabusca ().