English  |  正體中文  |  简体中文  |  Items with full text/Total items : 28611/40652
Visitors : 771711      Online Users : 44
RC Version 4.0 © Powered By DSPACE, MIT. Enhanced by NTU Library IR team.
Scope Adv. Search

Please use this identifier to cite or link to this item: http://ntour.ntou.edu.tw:8080/ir/handle/987654321/40803

Title: Artificial Neural Network Approach to Authentication of Coins by Vision-based Minimization
Authors: Jang-Ping Wang;Yi-Cih Jheng;Guo-Ming Huang;Jen-Hsien Chien
Contributors: 國立臺灣海洋大學:輪機工程學系
Keywords: Authentication of coins;Minimization path;Back-propagation neural network;Eigen-sections
Date: 2009-05-07
Issue Date: 2017-02-07T01:02:42Z
Publisher: Machine Vision and Applications
Abstract: Abstract:A new inspection system, consisting of two procedures for the authentication of coins, is proposed in this paper. In the first procedure, optimum image-matching positions are found by minimizing the matching error of the test coins with their prototype coins. The second procedure is the decision-making process that inspects the coins as genuine or spurious by the Back-Propagation Neural Network combined with the concept of eigen-section. Unlike the traditional approach based on gray-level values, the quantity (8 bits) of the color’s scale has been adopted. The discrimination results are presented and discussed in this study.
Relation: 22(1), pp.87-98
URI: http://ntour.ntou.edu.tw:8080/ir/handle/987654321/40803
Appears in Collections:[輪機工程學系] 期刊論文

Files in This Item:

File Description SizeFormat
art%3A10.1007%2Fs00170-013-4879-z.pdf693KbAdobe PDF7View/Open

All items in NTOUR are protected by copyright, with all rights reserved.


著作權政策宣告: 本網站之內容為國立臺灣海洋大學所收錄之機構典藏,無償提供學術研究與公眾教育等公益性使用,請合理使用本網站之內容,以尊重著作權人之權益。
網站維護: 海大圖資處 圖書系統組
DSpace Software Copyright © 2002-2004  MIT &  Hewlett-Packard  /   Enhanced by   NTU Library IR team Copyright ©   - Feedback