基于人工蜂群算法的考场作弊行为检测方法

2015 International Conference on Informative and Cybernetics for Computational Social Systems (ICCSS) Pub Date : 2015-08-01 DOI:10.1109/ICCSS.2015.7281161

Yongzheng Lin, Jin Zhou

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引用次数: 2

摘要

提出了一种基于人工蜂群算法的考场作弊行为检测方法。将运动目标检测问题转化为前景与背景颜色值的差函数。采用人工蜂群算法对目标函数进行优化。通过适当的阈值比较值将背景分量从序列图像中分离出来，成功提取运动目标轨迹。对真实监控图像进行仿真实验，结果表明，该方法能够较好地找到运动物体的轨迹，达到检测考场作弊行为的目的。

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Detection method for cheating behavior in examination room based on artificial bee colony algorithm

A detection method for cheating behavior in examination room based on artificial bee colony algorithm is presented. The problem of moving objects detection is transformed into the difference function of color value between foreground and background. Artificial bee colony algorithm is applied for optimizing the objective function. The background component is separated from the sequence images by value of comparing with proper threshold and the moving target track can be successfully extracted. Simulation experiments with real surveillance image show that the mothed can attain good results for finding the track of moving objects and achieve the purpose of detecting the cheating behaviors in examination room.

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来源期刊

2015 International Conference on Informative and Cybernetics for Computational Social Systems (ICCSS)

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