Modified kNN Algorithm for Improved Recognition Accuracy of Biometrics System Based on Gait

Abstract : The k-nearest neighbors classifier is one of the most frequently used. It has several interesting properties, though it cannot be used in utilitarian biometric systems. This paper proposes the modification of kNN algorithm which ensures correct work even in the case of an attempt at access to the system by unauthorized people. Work of the algorithm was tested on data presenting ground reaction forces (GRF), generated during human’s walk, obtained from measurements carried out on over 140 people. Differences between particular strides were determined with the Dynamic Time Warping (DTW). The recognition precision obtained was as high as 98% of biometric samples.
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Khalid Saeed; Rituparna Chaki; Agostino Cortesi; Sławomir Wierzchoń. 12th International Conference on Information Systems and Industrial Management (CISIM), Sep 2013, Krakow, Poland. Springer, Lecture Notes in Computer Science, LNCS-8104, pp.59-66, 2013, Computer Information Systems and Industrial Management. 〈10.1007/978-3-642-40925-7_6〉
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Marcin Derlatka. Modified kNN Algorithm for Improved Recognition Accuracy of Biometrics System Based on Gait. Khalid Saeed; Rituparna Chaki; Agostino Cortesi; Sławomir Wierzchoń. 12th International Conference on Information Systems and Industrial Management (CISIM), Sep 2013, Krakow, Poland. Springer, Lecture Notes in Computer Science, LNCS-8104, pp.59-66, 2013, Computer Information Systems and Industrial Management. 〈10.1007/978-3-642-40925-7_6〉. 〈hal-01496099〉

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