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A Centroid based Hough Transformation for Indian license plate skew detection and correction of IR and color images

机译:基于质心的霍夫变换,用于印度车牌偏斜检测以及红外和彩色图像的校正

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摘要

Skew Correction is a processing-stage between LP Localization and Character Segmentation in License Plate Recognition system used to identify a vehicle by its number plate. License plate is skewed in captured image due to the positioning of the vehicle with respect to the camera while capturing the LP image. The skewed license plate affects badly on the accurate character segmentation and recognition. After localization skew correction technique is applied in order to get correct character segmentation followed by character recognition. In this paper, a Centroid based Hough Transform technique is presented for skew correction of license plate which performs better than the other approaches of skew correction including Thresholding, Connected Component analysis, Hough Transform and Centroid method. The performance of the proposed algorithm has been tested on live captured LP images, yielding better performance in car license plate segmentation and hence the presented algorithm is good for all types of LP recognition applications due to its direct and simple approach with minimal computational time.
机译:偏斜校正是车牌识别系统中LP本地化和字符分割之间的一个处理阶段,用于通过车牌识别车辆。由于在捕获LP图像时车辆相对于摄像机的位置,牌照在捕获的图像中会倾斜。偏斜的车牌会严重影响准确的字符分割和识别。定位后,应用偏斜校正技术以获得正确的字符分割,然后进行字符识别。在本文中,提出了一种基于质心的霍夫变换技术,用于车牌的偏斜校正,其效果比其他阈值校正,连接分量分析,霍夫变换和质心法等偏斜校正方法要好。所提出算法的性能已经在实时捕获的LP图像上进行了测试,在车牌分割中表现出了更好的性能,因此,由于其直接,简单的方法且所需的计算时间最少,因此该算法对于所有类型的LP识别应用都是好的。

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