• Title/Summary/Keyword: projection Dept. of Electronic Control Engineering

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A Study On Face Feature Points Using Active Discrete Wavelet Transform (Active Discrete Wavelet Transform를 이용한 얼굴 특징 점 추출)

  • Chun, Soon-Yong;Zijing, Qian;Ji, Un-Ho
    • Journal of the Institute of Electronics Engineers of Korea SC
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    • v.47 no.1
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    • pp.7-16
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    • 2010
  • Face recognition of face images is an active subject in the area of computer pattern recognition, which has a wide range of potential. Automatic extraction of face image of the feature points is an important step during automatic face recognition. Whether correctly extract the facial feature has a direct influence to the face recognition. In this paper, a new method of facial feature extraction based on Discrete Wavelet Transform is proposed. Firstly, get the face image by using PC Camera. Secondly, decompose the face image using discrete wavelet transform. Finally, we use the horizontal direction, vertical direction projection method to extract the features of human face. According to the results of the features of human face, we can achieve face recognition. The result show that this method could extract feature points of human face quickly and accurately. This system not only can detect the face feature points with great accuracy, but also more robust than the tradition method to locate facial feature image.

Multiple Target Angle Tracking Algorithm with Efficient Equation for Angular Innovation (효율적으로 방위각 이노베이션을 구하는 다중표적 방위각 추적 알고리즘)

  • Ryu, Chang-Soo;Lee, Jang-Sik;Lee, Kyun-Kyung
    • Journal of the Institute of Electronics Engineers of Korea SC
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    • v.38 no.6
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    • pp.1-8
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    • 2001
  • Recently, Ryu et al. proposed a multiple target angle tracking algorithm using the angular innovation extracted from the estimated signal subspace. This algorithm obtains the angles of targets and associates data simultaneously. Therefore, it has a simple structure without data association problem. However it requires the calculation of the inverse of a real matrix with dimension (2N+1)${\times}$(2N+1) to obtain the angular innovations of N targets. In this paper, a new linear equation for angular innovation is proposed using the fact that the projection error is zero when the target steering vector is projected onto the signal subspace. As a result, the proposed algorithm dose not require the matrix inversion and is computationally efficient.

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