The face spoof detection is the approach which can detect spoofed face. The face spoof detection methods has various phases which include pre-processing, feature extraction and classification. The classification algorithm can classify into two classes which are spoofed or not spoofed. The KNN approach is used previously with the GLCM algorithm for the face spoof detection which give low accuracy. In this research work, the hybrid classification method is proposed which is the combination of random forest, k nearest neighbour and SVM Classifiers. The simulation outcomes depict that the introduced method performs more efficiently in comparison with the conventional techniques with regard to accuracy. Keywords: Face Spoof, KNN, Hybrid Classifier, GLCM
Because server client systems frequently store data and process data both on the client and on the server, this sort of system contingency planning should take into consideration potential system failures on the server of the client and communication of server to client elements. This article examines the basics of customer server architecture and its privacy, such as why customerserver architecture is required and superior to others. This paper discusses the problems of MCC (Mobile Country Code), privacy and the various tasks associated with online application safety. In this article, we examined the depth of the client's server architecture, where clients transmit the requests required by the users of logic modules and secure web logging against client logging in clients. With complete distribution applications which employ computer power wherever it is accessible and give information wherever it is necessary, everybody will in future be able to use inexpensive and efficient desktop technology. In future, owners and registered users will have access to information to avoid the need for expert systems developers and their complicated programming languages. Information will be captured at source and immediately made available in the future to authorized users.
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