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Proceedings Paper

Segmenting license plates in scene images through a multiresolution pyramid method
Author(s): Alexandru Postolache; Jacques G. Trecat
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Paper Abstract

Car identification is often necessary in traffic control, transport planning, origin-destination inquiries and so on. It can be reached by reading the license plate contents. Segmenting the plate is a critical preprocessing step for this. We present a multi-resolution plate segmentation algorithm, looking for constrained texture regions, and giving very high confidence to the final plate candidate, with no reading attempt. As real-time or near real-time execution are required in such traffic-based applications, a pyramidal approach is often necessary to reduce the amount of raw input data. Since vertical edges are critical in the plate detection, we created a new construction method emphasizing edges on the top level of the pyramid. The plate candidates are searched in between the textured regions on the top level of the pyramid and they are accepted or rejected, in function of various geometric criteria and some constrained texture regions features. Experiments, led on 405 outdoor scene images of static as well as moving cars under uncontrolled illumination, showed high accuracy and high scores in detecting the plate. Moreover our algorithm is dealing very well with cases with many character strings present in the image, and not only the one corresponding to the plate.

Paper Details

Date Published: 21 August 1996
PDF: 10 pages
Proc. SPIE 2786, Vision Systems: Applications, (21 August 1996); doi: 10.1117/12.248565
Show Author Affiliations
Alexandru Postolache, Faculte Polytechnique de Mons (Belgium)
Jacques G. Trecat, Faculte Polytechnique de Mons (Belgium)


Published in SPIE Proceedings Vol. 2786:
Vision Systems: Applications

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