[논문]Real-Time Container Shape and Range Recognition for Implementation of Container Auto-Landing System

Wei, Li; Lee, Eung-Joo

Real-Time Container Shape and Range Recognition for Implementation of Container Auto-Landing System 원문보기

멀티미디어학회논문지 = Journal of Korea Multimedia Society, v.12 no.6, 2009년, pp.794 - 803

Wei, Li (Department of Information Communication Engineering, TongMyong University) , Lee, Eung-Joo (Department of Information Communication Engineering, TongMyong University)

Abstract ▼ AI-Helper

In this paper, we will present a container auto-landing system, the system use the stereo camera to measure the container depth information. And the container region can be detected by using its hough line feature. In the line feature detection algorithm, we will detect the parallel lines and perpendicular lines which compose the rectangle region. Among all the candidate regions, we can select the region with the same aspect-ratio to the container. The region will be the detected container region. After having the object on both left and right images, we can estimate the distance from camera to object and container dimension. Then all the detect dimension information and depth inform will be applied to reconstruct the virtual environment of crane which will be introduce in this paper. Through the simulation result, we can know that, the container detection rate achieve to 97% with simple background. And the estimation algorithm can get a more accuracy result with a far distance than the near distance.

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가설 설정

b) Th준 contrast between the gray-levels of the characters and the background is greater than that of other noncharacters and the background. The chai_acters are either black on a white background or white on a black background.
c) The characters in the images are composed of both short vertical and horizontal line segments.
d) Th얀 non-character regions are composed of long horizontal and vertical line segments; long horizontal line segment옹 but short vertical line segments; or long vertical line segments but short horizontal line segments.

제안 방법

and algorithmic. Since we wanted to avoid such issues as optical distortion, shading problems, background problems, our simulation results serve to illustrate and compare the methods, rather than to give absolute accuracy figures.

이론/모형

information from the image. And for getting the edge image, we will smooth the image by using the Gaussian filter [8] to remove the noise in the image, and then use Canny algorithm [9] to extract all the edges from the no-noise image. This step can also be named pre-process approach, and the result is as shown in Fig 3.
The information can te obtained by using container de— taction method. But we cannot g_윲t the real dimension information just through the detection algorithm.

성능/효과

a) The character sizes of veliicle and container ID numbers in the captured image are in the pixel range from 16 to 64, and the width of the character strokes is greater than or equal to 3 pixels. These are the input parameters of the whole system.

참고문헌 (13)

D. Lagunovsky and S. Ablameyko, "Straight-line-based primitive extraction in grey-scale object recognition," Pattern Recognition Letters, Vol.20, No.10, pp. 1005-1014, Oct. 1999.

상세보기
C. Lin and R. Nevatia, "Building detection and descriptionfrom a single intensity image," Computer Vision and Image Understanding, Vol.72, No.2, pp. 101-121, 1998.

상세보기
W.-B. Tao, J.-W. Tian, and J. Liu, "A new approach to extract rectangle building from aerial urban images," International Conference on Signal Processing, pp. 143-146, 2002.
Y. Zhu, B. Carragher, F. Mouche, and C. Potter, "Automatic particle detection through efficient hough transforms," IEEE Transactions on Medical Imaging, Vol.22, No.9, pp. 1053-1062, Sep. 2003.

상세보기
Y. Zhu, Carragher, and C. Potter, "Fast detection of generic biological particles in cryo-em images through efficient hough transforms," In International Symposium for Biomedical Imaging, pp. 205-208, 2002.
J. Illingworth and j. Kittler, "A Survey of the Hough Transform," Computer Vision, Graphics and Image processing Vol.44, pp. 87-116, 1988.

상세보기
A. V. Nguyen, Y. Y. Choo and E. J. Lee, "Container Dimension Detection and 3D Modeling based on Stereo Vision," MITA 2008, pp. 207-210, Chiang Mai, Tailand, July 3-5 2008.
Deng, G. and Cahill, L.W., "An adaptive Gaussian filter for noise reduction and edge detection," Nuclear Science Symposium and Medical Imaging Conference, Vol.3, pp. 1615-1619, 31 Oct.- 6 Nov. 1993.
Kakarala R. and Hero A. O , "On achievable accuracy in edge localization," ICASSP-91, Vol.4, pp. 2545-2548, 14-17 Apr. 1991.
A. Scheenstra, A. Ruifrok , and R. Veltkamp, "A Survey of 3D Face Recognition Methods ," International Conference on Audio-and Video-based Biometric Person Authentication, Vol. LNCS 3546, pp. 891-899, NY, USA, July 2005.
Li Wei, E.J. Lee, " Improved Multi-pose 2D Face Recognition Using 3D Face Model with Camera Pose Estimation Approach and nD-PCA Recognition Algorithm," IEEE Conference on ICCIT '08, Vol.2, pp. 728-736, Nov.2008.
Rumelhart D.E., McClelland J.L. (1986), "Parallel Distributed Processing," MIT. Press.
Zhengwu Yuan and Dongli Huang, "A Novel RFID-based Shipping Containers Location and Identification Solution in Multimodal Transport," Electrical and Computer Engineering, pp. 267-272, 4-7 May. 2008.

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Real-Time Container Shape and Range Recognition for Implementation of Container Auto-Landing System 원문보기

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Real-Time Container Shape and Range Recognition for Implementation of Container Auto-Landing System 원문보기

Abstract ▼ AI-Helper

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