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Proceedings Paper

Character segmentation algorithm for recognition of vehicle license plate
Author(s): JennKwei Tyan; Claus Neubauer; Ljubisa Goganovic
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Paper Abstract

In the automated license plate recognition system, many reading errors are caused by inadequate character segmentation. In particular, character segmentation becomes difficult as the acquired vehicle images are seriously degraded. In this paper, we use computer vision techniques and propose a recognition-based segmentation method coupled with template matching and neural network. This will enhance the accuracy of the recognition system that aims to read automatically the German license plate. Algorithmic improvements for a projection-based segmentation are described here. In the preprocessing stage, plate tilt detection and position refinement methods are developed to prepare the data for later process. For separating touching characters, a discrimination function is presented based on a differential analysis of character contour distance. A conditionally recursive segmentation with the feedback of recognition is developed for effectively splitting touching characters and merging broken characters. We have implemented our algorithms in the intelligent camera system and obtained improvement for the recognition rate. Currently, the experiment conducted with greatly varying illumination conditions is shown at the recognition rate of an average of 92 %. Further improvement of the system is continuously undertaken for various data sets acquired under different environment conditions.

Paper Details

Date Published: 15 November 1999
PDF: 10 pages
Proc. SPIE 3838, Mobile Robots XIV, (15 November 1999); doi: 10.1117/12.369260
Show Author Affiliations
JennKwei Tyan, Siemens Corporate Research, Inc. (United States)
Claus Neubauer, Siemens Corporate Research, Inc. (United States)
Ljubisa Goganovic, Siemens Corporate Research, Inc. (United States)

Published in SPIE Proceedings Vol. 3838:
Mobile Robots XIV
Douglas W. Gage; Howie M. Choset, Editor(s)

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