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Development of a Face Detection and Recognition System Using a RaspberryPi (라즈베리파이를 이용한 얼굴검출 및 인식 시스템 개발)

  • Kim, Kang-Chul;Wei, Hai-tong
    • The Journal of the Korea institute of electronic communication sciences
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    • v.12 no.5
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    • pp.859-864
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    • 2017
  • IoT is a new emerging technology to lead the $4^{th}$ industry renovation and has been widely used in industry and home to increase the quality of human being. In this paper, IoT based face detection and recognition system for a smart elevator is developed. Haar cascade classifier is used in a face detection system and a proposed PCA algorithm written in Python in the face recognition system is implemented to reduce the execution time and calculates the eigenfaces. SVM or Euclidean metric is used to recognize the faces detected in the face detection system. The proposed system runs on RaspberryPi 3. 200 sample images in ORL face database are used for training and 200 samples for testing. The simulation results show that the recognition rate is over 93% for PP+EU and over 96% for PP+SVM. The execution times of the proposed PCA and the conventional PCA are 0.11sec and 1.1sec respectively, so the proposed PCA is much faster than the conventional one. The proposed system can be suitable for an elevator monitoring system, real time home security system, etc.