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Nanda Septiana
Telkom University
Computer Science & IT Electrical & Electronics Engineering

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Comparison Analysis of Gait Classification For Human Motion Identification Using Embedded Computer Agung Nugroho Jati; Astri Novianty; Nanda Septiana; Leni Widia Nasution
International Journal of Electrical and Computer Engineering (IJECE) Vol 8, No 6: December 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (221.854 KB) | DOI: 10.11591/ijece.v8i6.pp5014-5020

Abstract

In this paper, it will be discussed about comparison between two kinds of classification methods in order to improve security system based of human gait. Gait is one of biometric methods which can be used to identify person. K-Nearest Neighbour has parallelly implemented with Support Vector Machine for classifying human gait in same basic system. Generally, system has been built using Histogram and Principal Component Analysis for gait detection and its feature extraction. Then, the result of the simulation showed that K-Nearest Neighbour is slower in processing and less accurate than Support Vector Machine in gait classification.
Co-Authors Agung Nugroho Jati Leni Widia Nasution Novianty, Astri