• Title/Summary/Keyword: Smart phone Accelerometer

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Smart Phone Sensor-Based Indoor Location Tracking System for Improving the Location Error of the Radio Environment (무선 환경의 위치 정보 오차 개선을 위한 스마트폰 센서 기반 실내 위치 추적 시스템)

  • Lee, Dae-Young;Kang, Young-Heung
    • Journal of Advanced Navigation Technology
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    • v.19 no.1
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    • pp.74-79
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    • 2015
  • In this paper, in order to improve the error is utilized to location tracking the smart sensor detects a walking information user, RSSI is to provide an indoor position tracking system that is capable of correcting an error in terms weak. The acceleration sensor is able to detect the activity in the user walking and detects the number of step and the moving distance using the same. The Direction sensor is utilized as a digital compass, to detect the moving direction of the user. As a result of detecting the walking information using the sensor, it can be showed that this proposed indoor positioning system has a high degree of accuracy for the number of steps and the movement direction. Therefore, this paper shows that the proposed technique can correct the error of the location information to be problem in the conventional indoor location system which uses the only Wi-Fi APs by estimating the user's movement direction and distance using the sensors in smartphone without an additional equipment and cost.

Mobile Finger Signature Verification Robust to Skilled Forgery (모바일환경에서 위조서명에 강건한 딥러닝 기반의 핑거서명검증 연구)

  • Nam, Seng-soo;Seo, Chang-ho;Choi, Dae-seon
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.26 no.5
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    • pp.1161-1170
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    • 2016
  • In this paper, we provide an authentication technology for verifying dynamic signature made by finger on smart phone. In the proposed method, we are using the Auto-Encoder-based 1 class model in order to effectively distinguish skilled forgery signature. In addition to the basic dynamic signature characteristic information such as appearance and velocity of a signature, we use accelerometer value supported by most of the smartphone. Signed data is re-sampled to give the same length and is normalized to a constant size. We built a test set for evaluation and conducted experiment in three ways. As results of the experiment, the proposed acceleration sensor value and 1 class model shows 6.9% less EER than previous method.