Adaptive thresholds edge detection of traffic image

XIAO Wang-xin; ZHANG Xue; HUANG Wei

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XIAO Wang-xin, ZHANG Xue, HUANG Wei. Adaptive thresholds edge detection of traffic image[J]. Journal of Traffic and Transportation Engineering, 2003, 3(4): 104-107.

Citation:

XIAO Wang-xin, ZHANG Xue, HUANG Wei. Adaptive thresholds edge detection of traffic image[J]. Journal of Traffic and Transportation Engineering, 2003, 3(4): 104-107.

XIAO Wang-xin, ZHANG Xue, HUANG Wei. Adaptive thresholds edge detection of traffic image[J]. Journal of Traffic and Transportation Engineering, 2003, 3(4): 104-107.

Citation:

XIAO Wang-xin, ZHANG Xue, HUANG Wei. Adaptive thresholds edge detection of traffic image[J]. Journal of Traffic and Transportation Engineering, 2003, 3(4): 104-107.

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Adaptive thresholds edge detection of traffic image

1.
Center of ITS Research, Southeast University, Nanjing 210096, China
2.
Department of Computer Science and Engineering, Southeast University, Nanjing 210096, China

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Author Bio:
XIAO Wang-xin(1975-), male, doctoral student, 86-25-3793131, xzhangxue@seu.edu.cn
Received Date: 2003-01-28
Publish Date: 2003-04-25

Abstract

Abstract

The edge of traffic image was detected with wavelet transform. Its scale influence, meteyard and adaptive thresholds were studied. Large scale filter was used to restrain and identify noise, while small scale fiter was used to precisely position for image edge. A quadric B-spline wavelet was constructed, which has eminent characters, such as narrow support, small computation amount. Simulation results prove its effect is better than that of classical Sobel operator, the former method has good anti-noise and adaptive ability.
- traffic monitoring,
- wavelet transform,
- edge detection,
- quadric B-spline,
- adaptive thresholds

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References(7)

References

[1]	Canny J. A computational approach to edge detection[J]. IEEETrans., PAMI, 1986, 8(6): 679-698.
[2]	Fathy M, Siyal M Y. A window-based image processing tech-nique for quantitative and qualitative analysis of road traffic pa-rameters[J]. IEEE Trans., 1998, 47(4): 1342-1349.
[3]	Fathy M, Siyal M Y. Real-time image processing approach tomeasure traffic queue parameters[J]. IEE Proceedings-Vision, Image and Signal Processing, 1995, 142(5): 297-303.
[4]	Picton P D. Tracking and Segmentation of Moving Objects in aScene[M]. Warwick, UK, 1989.
[5]	Fathy M, Siyal M Y. An image detection technique based onmorphological edge detection and background differencing forreal-time traffic analysis[J]. Pattern Recognition Letters, 1995, 16(12): 1321-1330.
[6]	Ashworth R, Darkin D G, Dickinson K W, et al. Applications ofvideo image processing for traffic control systems[A]. SecondInternational Conference on Road Traffic Control[C]. London, UK, 1985.
[7]	Mallat S G, Zhong S. Characterization of signal from multi-scales edges[J]. IEEE Trans., PAMI, 1992, 14(7): 701-732.