摘要
针对人工录入纸质问卷中所存在的工作任务重、效率低、误差大等问题,提出一种基于标志点的纸质问卷设计方案及自动识别方法。在问卷的每个题目和选项前分别设置题目标志点和选项标志点,通过提取与区分标志点定位题目和选项,判断每个选项的答题区域是否存在答题标识,实现问卷结果的自动识别。100份问卷实验结果显示,本文方法对各种笔在答题框内画实心、空心圆圈、直线和对勾等均能正确识别,总体识别率为98.95%,每页问卷的平均识别时间为1.163s。本方法可以大幅提高纸质问卷分析效率、降低错误率、减少人力成本,为纸质调查问卷的统计提供了一种有效的自动识别方法。
To achieve the automatic statistics of paper questionnaires, a paper questionnaire design scheme based on mark points and the automatic identification of its answers are proposed. The title mark points and option mark points are set respectively in front of each question and the option in the questionnaire, by extracting and distinguishing the mark points to locate topics and options, and searching fill traces of respondents in answer area belonging to each option, so the automatic recognition is achieved. The experimental results show that the solid circles, hollow circles and check mark can all be correctly identified in the answer frame, but if they are drawn outside the area of answer, the recognition of check marks is easy to miss. The overall recognition rate of the check marks is 98. 95%, the average time for each questionnaire is 1. 163 s. This method can greatly improve the analysis efficiency and reduce the error rate and costs, so provde an effective automatic identification method for the statistics of the paper questionnaire.
作者
孟祥丽
吴涛
陈聘
MENG Xiang-li;WU Tao;CHEN Pin(School of Information Engineering,Lingnan Normal University,Zhanjiang 524048,Chin)
出处
《测控技术》
CSCD
2018年第8期32-35,45,共5页
Measurement & Control Technology
基金
国家自然科学基金项目(61402399)
广东省教育厅特色创新类项目(2017GXJK104)
岭南师范学院科研项目(LY1813)
关键词
纸质问卷
自动识别
标志点
计算机视觉
倾斜矫正
paper questionnaire
automatic identification
markpoint
computer vision
tilt correction