New Lane Detection Algorithm that Emulates Human Color Recognition

Hideyuki Saito; Kazuyuki Kobayashi; Kajiro Watanabe; Tetsuo Kinoshita

doi:10.20965/jrm.2015.p0382

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JRM Vol.27 No.4 pp. 382-391

doi: 10.20965/jrm.2015.p0382

(2015)

Paper:

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New Lane Detection Algorithm that Emulates Human Color Recognition

Hideyuki Saito, Kazuyuki Kobayashi, Kajiro Watanabe, and Tetsuo Kinoshita

Graduate School of Science and Engineering, Hosei University
3-7-2 Kajino-cho, Koganei, Tokyo 184-8584, Japan

Received:

January 20, 2015

Accepted:

June 10, 2015

Published:

August 20, 2015

Keywords:

mobile robot, lane detection, omnidirectional camera

Abstract

New lane detection algorithm

The perception of color by the human eye is different from that of cameras. This is due to the optical illusion and color constancy characteristics of human vision. In spite of these characteristics, people can drive cars without the danger of overturning. In this paper, we describe a new white lane detection algorithm for autonomous mobile robots, one based on a method similar to the color perception of human beings. In order to drive safely, we emulate human color perception to reduce the effects of lighting and shadow on the course. The validity of the proposed image compensation method is confirmed by actual while line detection.

Cite this article as:

H. Saito, K. Kobayashi, K. Watanabe, and T. Kinoshita, “New Lane Detection Algorithm that Emulates Human Color Recognition,” J. Robot. Mechatron., Vol.27 No.4, pp. 382-391, 2015.

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References

[1] K. Yamamoto, T. Okubo, Y. Ono, and Y. Hara, “Examples of Activities in the Background of the Field Test “Tsukuba Challenge” and Autonomous Mobile Technologies to Finish the Test,” Information Processing Society of Japan, Vol.52, No.9, pp. 1166-1172, 2011(In Japanese).
[2] E. H. Adelson, “Perceptual Organization and the Judgment of Brightness,” Science, Vol.262, pp. 2042-2044, 1993.
[3] B. A. Wandell, “Foundations of Vision,” Sinauer, 1995.
[4] J. K. Bowmaker and H. J. Dartnall, “Visual pigments of rods and cones in a human retina,” The J. of physiology, Vol.298, No.1, pp. 501-511, 1980.
[5] E. H. Land, “The retinex theory of color vision,” J. Opt. Soc. Am., Vol.61, pp. 1-11, 1977.
[6] R. S. Woodworth and R. Schlosberg, “Experimental Psychology,” Holt, Rinehard and Winston, 1954.
[7] L. T. Maloney, “Physics-based approaches to modeling surface color perception,” Color vision: From genes to perception, pp. 387-416, 1999.
[8] K. Devlin, “A review of tone reproduction techniques,” Technical Report, CSTR-02-005, Department of Computer Science, University of Bristol, 2002.
[9] K. Kobayashi, K. Watanabe, T. Ohkubo, and Y. Kurihara, “A Lane Detection Algorithm for Personal Vehicles,” Electrical Engineering in Japan, Vol.177, No.4, pp. 23-32, 2011.
[10] M. Amemiya, K. Ishikawa, K. Kobayashi, and K. Watanabe, “Lane detection for intelligent vehicle employing omni-directional camera,” SICE 2004 Annual Conf., Vol.3, pp. 2166-2170, 2004.
[11] A. Matsumoto, S. Tsukuda, and G. Yoshita, “Navigation of an Omnidirectional Mobile Robot by Teaching a Few Omnidirectional Images,” J. of Robotics and Mechatronics, Vol.16, No.1, pp. 80-89, 2004.
[12] M. Kristou, A. Ohya, and S. Yuta, “Target Person Identification and Following Based on Omnidirectional Camera and LRF Sensor Fusion from a Moving Robot,” J. of Robotics and Mechatronics, Vol.23, No.1, pp. 163-172, 2011.

This article is published under a Creative Commons Attribution-NoDerivatives 4.0 Internationa License.

[1] [1] K. Yamamoto, T. Okubo, Y. Ono, and Y. Hara, “Examples of Activities in the Background of the Field Test “Tsukuba Challenge” and Autonomous Mobile Technologies to Finish the Test,” Information Processing Society of Japan, Vol.52, No.9, pp. 1166-1172, 2011(In Japanese).

[2] [2] E. H. Adelson, “Perceptual Organization and the Judgment of Brightness,” Science, Vol.262, pp. 2042-2044, 1993.

[3] [3] B. A. Wandell, “Foundations of Vision,” Sinauer, 1995.

[4] [4] J. K. Bowmaker and H. J. Dartnall, “Visual pigments of rods and cones in a human retina,” The J. of physiology, Vol.298, No.1, pp. 501-511, 1980.

[5] [5] E. H. Land, “The retinex theory of color vision,” J. Opt. Soc. Am., Vol.61, pp. 1-11, 1977.

[6] [6] R. S. Woodworth and R. Schlosberg, “Experimental Psychology,” Holt, Rinehard and Winston, 1954.

[7] [7] L. T. Maloney, “Physics-based approaches to modeling surface color perception,” Color vision: From genes to perception, pp. 387-416, 1999.

[8] [8] K. Devlin, “A review of tone reproduction techniques,” Technical Report, CSTR-02-005, Department of Computer Science, University of Bristol, 2002.

[9] [9] K. Kobayashi, K. Watanabe, T. Ohkubo, and Y. Kurihara, “A Lane Detection Algorithm for Personal Vehicles,” Electrical Engineering in Japan, Vol.177, No.4, pp. 23-32, 2011.

[10] [10] M. Amemiya, K. Ishikawa, K. Kobayashi, and K. Watanabe, “Lane detection for intelligent vehicle employing omni-directional camera,” SICE 2004 Annual Conf., Vol.3, pp. 2166-2170, 2004.

[11] [11] A. Matsumoto, S. Tsukuda, and G. Yoshita, “Navigation of an Omnidirectional Mobile Robot by Teaching a Few Omnidirectional Images,” J. of Robotics and Mechatronics, Vol.16, No.1, pp. 80-89, 2004.

[12] [12] M. Kristou, A. Ohya, and S. Yuta, “Target Person Identification and Following Based on Omnidirectional Camera and LRF Sensor Fusion from a Moving Robot,” J. of Robotics and Mechatronics, Vol.23, No.1, pp. 163-172, 2011.