摘要
根据考场监控环境下存在利用云台可变焦摄像机获取考试试卷进行泄题的可能性,提出了一个基于图像处理和模式分类技术的作弊试卷检测方法。首先通过阈值初选策略进行试卷像素初检,并采用自适应的高斯混合模型使检测结果进一步适应不同的光照和场地,然后利用区域分析和增长技术消除检测噪音并形成区域,最后提取多个形状描述特征对检测到的区域进行分类,得到泄题试卷。通过广泛的定量和定性的实验分析验证了该方法的性能和效率。
In order to avoid cheating examinations by using camera pan and tilt,a method of detecting examination paper is proposed by using image processing and pattern classification techniques under surveillance environment.Firstly,a thresholding pre-selection strategy is used to detect possible paper pixels,and adaptive Gaussian Mixture Models is trained to adapt different illumination and place conditions;then region growing technique is proposed to remove noises;and finally several shape description features are computed to classify the detected regions to obtain the final detection result.Extensive quantitative and qualitative experimental evaluations validate the performance and efficiency of the proposed method.
出处
《计算机工程与应用》
CSCD
北大核心
2010年第32期244-248,共5页
Computer Engineering and Applications
基金
北京市科学技术委员会课题(No.Z08030103610803)~~
关键词
泄题试卷检测
视频监控
高斯混合模型
区域增长
形状分类
detecting examination paper； video surveillance； Gaussian mixture model； region growing； shape classification；
