车牌倾斜校正 英文原文及翻译

英文原文及中文翻译

（一）英文原文

One: A Method of Slant Correction of Vehicle License Plate

Based on Watershed Algorithm

In a vehicle license plate recognition system, slant vehicle license plate has a bad effect on the character segmentation and recognition. A method of slant correction of vehicle license plate is proposed in this paper. The method consists of five main stages: (1) the extraction of the boundaries of characters using watershed algorithm;

(2) dividing the boundaries of vehicle license plate into small segments using vertical

differential method; (3) connection of the fracture characters using expansion and corrosion; (4) computing centroids of the left and the right part in the vehicle license plate respectively; (5) finding the slant angle by means of two centroids. Experimental results show that the error rate of using the method is 6.13%, which is lower than that of the principal component analysis. The running time of using this method is less than that of Hough transform. The method improves accuracy of the slant correction.

With the rapid development of highways and the wide use of vehicles, people have started to pay more and more attention on vehicle license plate recognition system.

Vehicle license positioning, extraction and character segmentation are one of the most difficult topics in the vehicle license plate recognition system. Slant vehicle license plate has a bad effect on the character segmentation and recognition. In the last few years some achievements in vehicle license positioning and slant correction have been obtained. These achievements have distinguished effects in special conditions.

However, under a complex background, the effect of slant correction needs to be enhanced further. Many problems such as: small contrast, non-uniform illumination, image distortion as well as the contaminate dlicense plate and so on may bring difficulty in slant correction of vehicle license plate. This article presents a method (called SCWA method) of slant correction of vehicle license plate based on watershed algorithm. As documented in the experiments of 460 vehicle license plates, the error rate of using the SCWA method is 6.13%, which is lower than that of the principal component analysis. The running time of using SCWA method is less than that of Hough transform. Good slant correction is achieved with SCWA method. The paper is outlined as follows: section I presents the introduction, section II describes the SCWA method and section III presents a conclusion of the experiments of 460 vehicle license images.

II. SCWA METHOD

A. Extraction of the Boundaries of Characters Using

Watershed Algorithm There are many boundaries of characters in the vehicle