摘要
为利用Resnet50网络对三枚同源激光雕刻塑胶印章盖印的印文进行鉴别,通过使用pytorch框架运行Resnet50开源网络模型,制作激光扫描速度分别为210、280、350的三枚同源塑胶印章,盖印15000枚印文,扫描得到印文图像作为训练数据,盖印100枚扫描作为测试数据。研究了以改变训练样本量得到的Resnet50网络模型对同源印章印文鉴别的准确率。结果表明:网络最终收敛能成功学习特征,以150-15000枚的印文图像训练得到的准确率能达到95.66%-99.789%,对300枚印文图像测试得到94.6%以上的准确率。可见利用Resnet50对同源激光雕刻塑胶印章印文进行鉴别是一种可行的方法。
In order to identify the seals stamped by three homologous laser engraved plastic stamps using the Resnet50 network, three reciprocal plastic stamps with laser scanning speeds of 210, 280 and 350 were produced by running the Resnet50 open source network model using the pytorch framework. A stamp of 15,000 stamps was scanned to obtain a printed image as training data, and 100 scans were stamped as test data. The accuracy of the Resnet50 network model obtained by changing the training sample size for the identification of the same-same seal is studied.The results show that the final convergence of the network can successfully learn the characteristics. The accuracy of the training of 150-15 000 printed images can reach 95.66%-99.789%, and the accuracy of 94.6% of the 300 printed images is obtained. It is concluded that it is a feasible method to identify the homologous laser engraving plastic seal stamp by using Resnet50.
作者
张倩
郝红光
王长亮
吕晨
韩星周
ZHANG Qian;HAO Hong-guang;WANG Chang-liang;LV Chen;HAN Xing-zhou
出处
《信息技术与信息化》
2019年第5期123-126,共4页
Information Technology and Informatization
基金
国家重点研发计划课题2016YFC0801104
财政部基本科研业务费2018JB022资助