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The Monitoring System Of On-line Exam Based On The Imange Analysis

Posted on:2012-06-28Degree:MasterType:Thesis
Country:ChinaCandidate:L FengFull Text:PDF
GTID:2178330335451422Subject:Computer Science and Technology
Abstract/Summary:PDF Full Text Request
On-line examination is being used by more and more schools, enterprises, social organizations in order to inspect students, employees or other relevant personnel as a new kind of examination method. Compared with the traditional testing form, on-line examination has its unique advantages, such as the reduced work of exam preparation, meeting the needs of high frequency of examination anywhere at anytime. That the machine correcting the examination paper, greatly reduced the teacher's work pressure. Due to the characteristics of on-lne exam network, examinee can remote to the exam, thus reducing the burden of the examinees. Although on-line examination has these advantages, compared with the traditional test, there are also some new problems, especially the diversification of the cheating way. The examinee can cheat through the im chatting tools, network sharing, bringing electronic devices, asking someone else to attend the exam instead of themselves. All this brings a great impact on the on-line examination.This topic is about the exam monitoring system based on image analysis, and is mainly aimed at some cheating ways,—asking someone else to take the exam instead of themselves, whisper cheating and leaving their seats without permit, from the angle of image to ensure the security and fairness of on-line exam. This paper mainly introduced the development condition of on-line exam system and the problems. All it expounds the important significance of the application of combining the video monitoring and image analysis into the on-line exam system.The paper introduces design scheme of the system, technology and image processing algorithm. The technology includes Activex plug-in technology, XML, TCP Socket communication mode. And for the image processing, the main methods is Adaboost face detection and hidden markov model face recognition method. System uses modular design method, and is mainly divided into video monitoring module, image analysis module, data communication module and the information storage module, etc.
Keywords/Search Tags:Online exam, Video monitoring, Hidden Markov Model(HMM), Adaboost algorithm, ActiveX plug-in technology
PDF Full Text Request
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