Journal of the Korea Society of Computer and Information (한국컴퓨터정보학회논문지)

Korean Society of Computer Information (한국컴퓨터정보학회)
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A Study on Finding the Rail Space in Elevators Using Matched Filter

  • Song, Myong-Lyol (Dept. of Information & Communication Eng., Hoseo University)
  • Received : 2019.03.28
  • Accepted : 2019.05.29
  • Published : 2019.06.28
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Abstract

In this paper, we study on finding the rail space in elevators by analyzing each image captured with CCD camera. We propose a method that applies one-dimensional matched filter to the pixels of a selected search space in the vertical line at a horizontal position and decides the position with the thickness of the space being represented by a black thick line in captured images. The pattern similarity representing how strongly the associated image pixels resemble with the thick line is defined and calculated with respect to each position along the vertical line of pixels. The position and thickness of the line are decided from the point having the maximum in pattern similarity graph. In the experiments of the proposed method under different illuminational conditions, it is observed that all the pattern similarity graphs show similar shape around door area independent of the conditions and the method can effectively detect the rail space if the rails are illuminated with even weak light. The method can be used for real-time embedded systems because of its simple algorithm, in which it is implemented in simple structure of program with small amount of operations in comparison with the conventional approaches using Canny edge detection and Hough transform.

Keywords

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Fig. 1. Matched filter operation

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Fig. 2. Image captured by the camera

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Fig. 3. Grey level representation of the pixels in the rectangular area in Fig. 2

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Fig. 4. G(320,y) : Grey level of the pixels at line x=320

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Fig. 5. The concept of finding the rail space using matched filter

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Fig. 6. The top view of the experimental environment

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Fig. 7. x=320, [y1, y2] = [140, 440], (L1, L2) = (ON, ON)

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Fig. 8. Pattern similarity Ci (xa, k) : x=320, [y1, y2]=[140, 440], (L1, L2) = (ON, ON)

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Fig. 9. x=320, [y1, y2] = [140, 440], (L1, L2) = (OFF, OFF)

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Fig. 10. Pattern similarity Ci(xa,k) : x=320, [y1, y2] = [140, 440], (L1, L2) = (OFF, OFF)

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Fig. 11. x=320, [y1, y2] = [300, 400], (L1, L2) = (OFF, OFF)

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