• 제목/요약/키워드: KLT operator

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Registration of Aerial Video Frames for Generating Image Map (영상지도제작을 위한 항공 비디오 영상 등록)

  • Kim, Seong-Sam;Shin, Sung-Woong;Kim, Eui-Myoung;Yoo, Hwan-Hee
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.25 no.4
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    • pp.279-287
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    • 2007
  • The increased availability of portable, low-cost, high resolution video equipments have resulted in a rapid growth of the applications for video sequences. These video devices can be mounted in handhold unit, mobile unit and airborne platforms like maned or unmaned helicopter, plane, airship, etc. This paper describes the feasibility fur generating image map from the experimental results we designed to track the interested points extracted by KLT operator in the neighboring frames and implement image matching for each frames taken from UAV (Unmaned Aerial Vehicle). In the image registration for neighbourhood frames of aerial video, the results demonstrate the successful rate of matching slightly decreases as the drift between frames increases, and also that the stable photographing is more important matching condition than the pixel shift.

Visual inspection algorithm of cold rolled strips by wavelet frame transform (Wavelet frame 변환을 이용한 냉연 시각검사 알고리듬)

  • Lee, Chang-Su;Choi, Jong-Ho
    • Journal of Institute of Control, Robotics and Systems
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    • v.4 no.3
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    • pp.372-377
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    • 1998
  • This paper deals with the detection, feature extraction and classification of surface defects in cold rolled strips. Inspection systems are one of the most important fields in factory automation. Defects such as slipmark and dullmark can be effectively detected with a Gaussian matched filter because their shapes are similar to Gaussian. It is justified that the proposed WF(Wavelet Frame) method could be regarded as multiscale Gaussian matched filter which can be applied to the inspection of cold rolled strip. After a wavelet frame transform, the entropies and moments are computed for each subband which pass through both local low pass filter and nonlinear operator. With these features as input, a MLP(Multi Layer Perceptron) is used as a classifier. The proposed inspection method was applied to the real images with defects, and hence showed good performance. The role of each extracted feature is analyzed by KLT(Karhunen-Loeve Transform).

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