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一种适用于移动设备在线阅卷的答题卡自动识别算法
引用本文:孙琳,张琪,罗念祖,邓书勤,陈念年.一种适用于移动设备在线阅卷的答题卡自动识别算法[J].计算机测量与控制,2018,26(10):255-259.
作者姓名:孙琳  张琪  罗念祖  邓书勤  陈念年
作者单位:西南科技大学计算机科学与技术学院 四川绵阳,西南科技大学计算机科学与技术学院 四川绵阳,西南科技大学计算机科学与技术学院 四川绵阳,西南科技大学计算机科学与技术学院 四川绵阳,西南科技大学计算机科学与技术学院 四川绵阳
基金项目:四川省教育厅科技成果转化重大培育项目(14zd1102);西南科技大学龙山学术人才科研支持计划(17LZX425);西南科技大学研究生创新基金资助(17ycx053);
摘    要:基于智能移动设备的阅卷方式无需专用设备即可快速阅卷,降低成本的同时还能增加阅卷工作的可移动性。为解决移动设备拍照阅卷时,出现的阴影、反光、倾斜(-45°~45°)等情况,设计并实现了一套答题卡自动识别算法,算法主要分为三部分:图像预处理、待识别区域定位与分割、答题卡内容识别。不同操作系统(PC、Android、IOS)下测试结果表明:该算法正常填涂采集识别率为100%,异常填涂采集识别率为93.6%;识别速度小于2s,满足实时性要求;无需修改就能在不同操作系统下编译运行,提高了程序的通用性和兼容性。目前该算法已成功应用于某教育企业上线APP中。

关 键 词:自动阅卷  跨平台  答题卡识别  图像预处理
收稿时间:2018/4/3 0:00:00
修稿时间:2018/4/24 0:00:00

An automatic recognition algorithm for the online marking of mobile devices
ZHANG Qi,Luo Nianzu,Deng Shuqin and.An automatic recognition algorithm for the online marking of mobile devices[J].Computer Measurement & Control,2018,26(10):255-259.
Authors:ZHANG Qi  Luo Nianzu  Deng Shuqin and
Affiliation:School of Computer Science and Technology,Southwest University of Science and Technology,School of Computer Science and Technology,Southwest University of Science and Technology,School of Computer Science and Technology,Southwest University of Science and Technology,School of Computer Science and Technology,Southwest University of Science and Technology,
Abstract:The marking method which based on intelligent mobile device can work fast without special equipment, reduce costs and increase the mobility of marking work. To solve the problem when using a mobile device for marking, such as shadows, reflections, tilted -45° to 45° and so on, this article designed and implemented a set of sheet automatic identification algorithm. The algorithm is mainly divided into three parts: image preprocessing, identify regional orientation and segmentation, sheet content recognition. Experimental results show in different operating systems (PC, Android, IOS): the recognition rate of the algorithm is 100%, and the detection rate of abnormal filling is 93.6%; the recognition speed is less than 2s, satisfying the real-time requirement; it can be compiled and run under different operating systems without modification, thus improving the universality and compatibility of the program.At present, this algorithm has been successfully applied to a education enterprise on-line APP.
Keywords:automatic marking  cross-platform  exam card recognition  image pre-processing
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