Research and Improvement on Fast Location Algorithm in License Plate

Abstract:

In the recognition system of license plate, the detection effect is often influenced by the speed of vehicle, the weather and illumination condition. However, the image edge is less influenced by the above conditions, so it gets more and more attention by using edge detection method to detect license plate. In this paper, three kinds of edge detection method based on partial derivative are compared. Firstly, using the first derivative to get the point set of gray step is discussed and thus the edge is obtained. However, this methods' result is largely influenced by noise. Secondly, adopting denosing theory and second partial derivative to acquire the image edge is represented, but the result shows that this method would filter out some high frequency edges and lead to the edge loss. Finally, the improved algorithm that is the fusion of three aspects: denosing theory, the second partial derivative and linking isolated edge points, is put forward. The result shows that the third algorithm has strong ability to restrain noise. However, at the same time it would smooth some high frequency edges out and lead to the edge loss. However, the third method finally makes isolated points link together, which ensure the integrity of the edge. Therefore, the result obtained by the second partial algorithm is better than the results by the two previous algorithms.

• Periodical: Applied Mechanics and Materials (Volumes 543-547)
• Pages: 2792-2795
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.543-547.2792
• Online since: March 2014
• Authors: Hong Hai Liu*, Xiang Hua Hou
• Keywords: Edge Point, Image De-Noising, LOG Operator, Second Derivative (SD)

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