面向嵌入式应用的货币智能鉴别关键技术研究

项目名称： 面向嵌入式应用的货币智能鉴别关键技术研究

项目编号： No.61272147

项目类型： 面上项目

立项/批准年度： 2013

项目学科： 自动化技术、计算机技术

项目作者： 贺建飚

作者单位： 中南大学

项目金额： 81万元

中文摘要： 货币鉴别技术是各类金融自助服务以及银行业务货币鉴别设备的共性关键技术，其内容包括纸币的真伪、面额、新旧、残缺、朝向、版本识别等。目前国内外嵌入式货币鉴别应用普遍存在着鉴别接收率较低、误辨率较高、鉴别速度较慢等三大主要问题。为此，本课题研究货币防伪检测技术新方法，通过引入计算触觉技术来检测货币纸质特征，进一步拓展货币特征信息维度；同时，研究残损纸币的图像退化模型及恢复方法，从而提高在鉴别过程中的自适应性；以上两方面的研究成果将有望提高鉴别接收率，并降低误辨率。此外，针对嵌入式应用背景，将研究完善货币全息特征信息提取与高效表示方法，构建一个有机、开放、长生命周期的货币全息特征数据模型；并基于该全息特征数据模型，研究典型嵌入式应用背景下的并行最优鉴别算法，提高鉴别速度。本项目的研究成果将有望为嵌入式应用背景下货币的快速、可靠鉴别提供理论指导和方法指导。

中文关键词： 货币识别；鉴别算法；货币特征模型；嵌入式系统；

英文摘要： Paper currency identification techniques, which conclude banknote's authenticity, denomination, old or new, impairment, orientation and series, are the common key techniques applied in financial self-service and paper currency recognition devices. There are three main problems in embedded paper currency identification such as low rate of identification to receive, high rate of error resolution, and low recognition speed. So, this project will perform research from aspects listed below. First, by trying to introduce tactile computing technology to detect characteristics of paper currency,it will study new currency counterfeiting detection technology to further expand the currency dimension feature information.Second, it will study damaged banknote's image degradation model and recovery method so as to increase self-adaptiveness in the identification process. These two research results may be helpful to increase the receive rate and reduce the error rate. Third, aiming at the embedded application background, by studying the currency holographic feature information extraction and efficient representation method, it will build an organic, open, long-life-cycle currency holographic features data model. Based on this model, it will study the parallel optimal identification algorithm to improve the identification rate.

英文关键词： banknote recognition；Identification algorithm；Currency characteristic model；embedded system；