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首页>《中国测试》期刊>本期导读>AlexNet两光照下多类别法定货币识别技术

AlexNet两光照下多类别法定货币识别技术

65    2019-09-29

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作者:刘思洋1, 黄坚1, 刘桂雄1, 罗文佳2

作者单位:1. 华南理工大学机械与汽车工程学院, 广东 广州 510640;
2. 广州市银科电子有限公司, 广东 广州 510663


关键词:法定货币;图像识别;深度学习;AlexNet


摘要:

基于法定货币在不同光照下部分特征不同,该文研究一种基于AlexNet的两光照下多类别法定货币识别技术。首先,分析自然光照、紫外光照下法定货币图像特征,指出不同光照下法定货币出现不同的面额、图案等特征;其次,分析AlexNet神经网络模型与研究面向法定货币识别的AlexNet迁移学习方法;最后,在30类别的两光照下不同币种的图像样本库上进行图像识别实验,货币图像识别准确率达到100%,准确实现区分货币币种、光照条件、面额与正反面货币图像功能。与经典货币图像识别方法相比,该法能减少人工提取图像特征的工作量,具有通用性好、准确度高的特点。


Technology of multi-category legal currency identification under multi-light conditions based on AlexNet
LIU Siyang1, HUANG Jian1, LIU Guixiong1, LUO Wenjia2
1. School of Mechanical and Automotive Engineering, South China University of Technology, Guangzhou 510640, China;
2. Guangzhou Yin Ke Electronics Co., Ltd., Guangzhou 510663, China
Abstract: Based on the difference of local characteristics of legal currency under different illuminations, this paper studies a multi-category legal currency recognition technology based on AlexNet. Firstly, the characteristics of legal currency images under natural light and ultraviolet light are analyzed. It is pointed out that the legal currency presents different fetures and patterns under different illuminations. Secondly, the AlexNet neural network model and the AlexNet migration learning method for legal currency identification are analyzed. Finally, On the image sample library of different currencies under 30 kinds of illumination, the image recognition experiment is carried out, and the accuracy of currency image recognition reaches 100%, which accurately realizes the functions of distinguishing the kinds of currency, lighting conditions, denomination and front and back currency images. Compared with the currency image recognition method, the workload of manually extracting image features can be reduced, and the utility model has the advantages of good versatility and high accuracy.
Keywords: legal currency;image identification;deep learning;AlexNet
2019, 45(9):118-122  收稿日期: 2018-08-22;收到修改稿日期: 2018-09-29
基金项目: 广州市科技计划项目(2018020300006)
作者简介: 刘思洋(1995-),男,广东揭阳市人,硕士研究生,专业方向为精密检测与仪器仪表
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