[1]朱德意,孙晴艺,董思凡,等.基于 OpenCV 的芯片 IMEI 码的检测与识别[J].计算机技术与发展,2022,32(08):174-179.[doi:10. 3969 / j. issn. 1673-629X. 2022. 08. 028]
　ZHU De-yi,SUN Qing-yi,DONG Si-fan,et al.Detection and Recognition of Chip IMEI Code Based on OpenCV[J].,2022,32(08):174-179.[doi:10. 3969 / j. issn. 1673-629X. 2022. 08. 028]
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基于 OpenCV 的芯片 IMEI 码的检测与识别()

《计算机技术与发展》[ISSN:1006-6977/CN:61-1281/TN]

卷:
32
期数:
2022年08期
页码:
174-179
栏目:
应用前沿与综合
出版日期:
2022-08-10

文章信息/Info

Title:
Detection and Recognition of Chip IMEI Code Based on OpenCV
文章编号:
1673-629X(2022)08--0174-06
作者:
朱德意1; 孙晴艺1; 董思凡1; 麻胜恒2; 王耀雄3; 高 放1
1. 广西大学 电气工程学院,广西 南宁 530004;
2. 广西中科阿尔法科技有限公司,广西 南宁 530201;
3. 中国科学院合肥智能机械研究所,安徽 合肥 230031
Author(s):
ZHU De-yi1; SUN Qing-yi1; DONG Si-fan1; MA Sheng-heng2; WANG Yao-xiong3; GAO Fang1
1. School of Electrical Engineering,Guangxi University,Nanning 530004,China;
2. Guangxi CT UNITE Alpha Technology Co. ,Ltd. ,Nanning 530201,China;
3. Institute of Intelligent Machines,Chinese Academy of Sciences,Hefei 230031,China
关键词:
IMEI; OpenCV; Tesseract-OCR; 运动目标; 字符识别; CRNN
Keywords:
IMEI; OpenCV; Tesseract-OCR; moving target; character recognition; CRNN
分类号:
TP510;TP751
DOI:
10. 3969 / j. issn. 1673-629X. 2022. 08. 028
摘要:
运动目标的检测与识别一直是计算机视觉的热点研究方向。 随着计算机技术的大力发展,机器能够与运动目标检测很好地结合,有望代替人们去完成那些枯燥乏味或者是危及生命安全的工作。 在芯片制造流水线中,依靠人工识别并记录芯片国际移动设备识别码(international mobile equipment identity,IMEI),效率低下且易出错。 为实现芯片 IMEI 码的自动识别,该文使用 OpenCV 对视频进行预处理,通过灰度化提取芯片上的全部轮廓,通过膨胀、腐蚀操作处理轮廓,再通过面积和周长两个参量筛选得到芯片的 IMEI 码区域,进一步通过将该区域与原视频结合得到含有芯片 IMEI 码的视频,最后使用 Tesseract-OCR 识别芯片 IMEI 码。 同时做了基于神经网络 CRNN 进行识别的对比实验,首先通过生成器函数构造了一个由字母、数字和冒号组成的数据集用于模拟芯片 IMEI 码输入 CRNN 网络进行预训练,在此基础上用 15 张IMEI 码的图片进行迁移学习,最后基于学习到的新模型对视频中的三块芯片进行识别。 通过对比发现,在小样本数据集的情况下,该方法识别芯片 IMEI 的准确率远远超过 CRNN 识别芯片 IMEI 码的准确率。
Abstract:
The detection and recognition of moving targets has always been a hot research topic of computer vision. With the vigorous development of computer technology,machines can be well integrated with moving target detection to hopefully replace people to completethose boring or life-threatening tasks. In the chip manufacturing pipeline,the identification and recording of the chip international mobileequipment identity (IMEI) is finished manually,which is inefficient and error-prone. In order to realize the automatic identification ofthe chip IMEI code,we use OpenCV to preprocess the video,extract all the contours on the chip through grayscale lithography,processthe contours through expansion and corrosion operations,and then filter through the two parameters of area and perimeter to obtain thechip’s IMEI code region,which is further combined with the original video to obtain a video containing the chip IMEI code. Finally,Tesseract-OCR is used to identify the chip IMEI code. At the same time,a comparison experiment of identifying IMEI codes with theCRNN network is performed. A data set composed of letters,numbers and colons is constructed through the generator function and fed into the network for pre-training. Transfer learning is used to transfer the knowledge learning from the above artificial dataset to a smalldataset containing 15 real IMEI code images. The optimized model is used to identify the IMEI codes of the three chips in the video. Itis found that the accuracy rate of the proposed OpenCV-based method to identify IMEI codes exceeds that of the CRNN network in caseof small training datasets.

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[1]于勇 张晖 林茂松.基于双目立体视觉三维重建系统的研究与设计[J].计算机技术与发展,2009,(06):127.
　YU Yong,ZHANG Hui,LIN Mao-song.Research and Design of the 3D Reconstruction System Based on Binocular Stereo Vision[J].,2009,(08):127.
[2]罗勤 曾致远 李波.桥墩安全监测系统中背景重建技术的研究[J].计算机技术与发展,2006,(06):23.
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[4]晁衍凯 徐昱琳 杨永焕.基于嵌入式Linux的视觉伺服系统设计[J].计算机技术与发展,2012,(05):6.
　CHAO Yan-kai,XU Yu-fin,YANG Yong-huan.Embedded Linux Based Visual Servo System Design[J].,2012,(08):6.
[5]徐自越 李战明 李二超.OpenCV在焊缝实时检测与处理系统中的应用[J].计算机技术与发展,2012,(08):170.
　XU Zi-yue,LI Zhan-ming,LI Er-chao.Application of OpenCV on Real-time Detection and Processing System of Seam[J].,2012,(08):170.
[6]胡顾飞,严毅.基于Adaboost算法的车辆轮胎检测研究与实现[J].计算机技术与发展,2013,(09):227.
　HU Gu-fei[],YAN Yi[].Research and Realization on Vehicle Tire Detecting Based on Adaboost Algorithm[J].,2013,(08):227.
[7]黄景星,吴伟隆,龙楚君,等.基于OpenCV的视频运动目标检测及其应用研究[J].计算机技术与发展,2014,24(03):15.
　HUANG Jing-xing,WU Wei-long,Long Chu-jun,et al.Study of Moving Object Detection in Video and Its Application Based on OpenCV[J].,2014,24(08):15.
[8]夏雪婷,胡正飞,潘玲云. 基于OpenCV人脸检测的室内照明自动控制系统[J].计算机技术与发展,2017,27(04):184.
　XIA Xue-ting,HU Zheng-fei,PAN Ling-yun. Indoor Automatic Lighting Control System with OpenCV Face Detection[J].,2017,27(08):184.
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　WANG Zhen,WU Fang,LU Liang-gang,et al. Research on Car Simulation System Based on Sight Control[J].,2017,27(08):116.
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更新日期/Last Update: 2022-08-10