Abstract
The robust and reliable recognition of traffic signs from a moving car is investigated as a specific example of the general ambitious goal of object recognition in natural surroundings. The newly proposed method of hierarchical spatial feature matching is employed, based on a pyramid representation of the scene and its local orientations. The worked example of designing a suitable template for “right-of-way” -signs (diamonds, rotated squares) illustrates some general principles of hierarchical feature matching. Hardware considerations indicate that the problem can be solved in real-time with a data-flow architecture using commercially available matching ICs. The performance with video imagery taken from a moving car (day and night, city and country scenes) is reported and some practical problems encountered are discussed. It is concluded that this non-AI based approach to traffic sign recognition is reliable, simple, fast and performs very well in real-life situations.
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References
R.E. Gämlich and W. Ritter, “A knowledge based system for traffic sign recognition”, Informatik-Fachberichte, Vol. 254, pp. 82–89, Springer, 1990.
E.H. Adelson, C.H. Anderson, J.R. Bergen, P.J. Burt and J.M. Ogden, “Pyramid methods in image processing”, RCA Engineer, Vol. 29, pp. 33–41, Nov./Dec. 1984.
P.J. Burt, “Smart Sensing with a Pyramid Vision Machine”, Proc. IEEE, Vol. 76, pp. 1006–1015, 1988.
P. Seitz and G.K. Lang, “Using local orientation and hierarchical spatial feature-matching for the robust recognition of object”, Proc. SPIE, Vol. 1606, in print, 1991.
P. Seitz, “The robust recognition of object primitives using local axes of symmetry”, Signal Processing, Vol. 18, pp. 89–108, 1989.
G. Kanizsa, “Subjective contours”, Scientific American, April 1976, pp. 82.
E.C. Freuder, “A Computer Vision System for Visual Recognition Using Active Knowledge”, M.I.T. A.I. Lab. Technical Report 345, 1975.
M. Bichsel, “Strategies of Robust Object Recognition for the Automatic Identification of Human Faces”, Dissertation No. 9467, ETH Zürich, 1991.
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© 1991 Springer-Verlag Berlin Heidelberg
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Seitz, P., Lang, G.K., Gilliardt, B., Pandazis, J.C. (1991). The robust recognition of traffic signs from a moving car. In: Radig, B. (eds) Mustererkennung 1991. Informatik-Fachberichte, vol 290. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-08896-8_37
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DOI: https://doi.org/10.1007/978-3-662-08896-8_37
Publisher Name: Springer, Berlin, Heidelberg
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