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Real-time license plate localisation on FPGA

机译:FPGA上的实时许可证板本地化

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Automatic Number Plate Recognition (ANPR) systems have become an important tool to track stolen car, access control and monitor the traffic. The fundamental requirements of an ANPR system are image capture using an ANPR camera, and processing of the captured image. The image processing part, which is a computationally intensive task, includes two stages i.e. plate localisation and character recognition. This paper presents an improved license plate localisation (LPL) algorithm based on modified Sobel vertical edge detection operator and two morphological operations suitable for FPGA implementation. The algorithm has been successfully implemented on a Xilinx Virtex-4 FPGA and tested using a database of 1000 images that contains UK number plates. It consumes 28% of the available on-chip resources, runs with a maximum frequency of 114.20 MHz, has a detection rate of 99.1% and capable of processing one image (640×480) in 3.8ms.
机译:自动编号板识别(ANPR)系统已成为跟踪被盗汽车,访问控制和监控流量的重要工具。 ANPR系统的基本要求是使用ANPR相机的图像捕获,以及处理捕获的图像。 作为计算密集型任务的图像处理部分包括两个阶段I.E.板本地化和字符识别。 本文提出了一种基于改进的Sobel垂直边缘检测操作员的改进的牌照定位(LPL)算法,以及适用于FPGA实现的两种形态操作。 该算法已在Xilinx Virtex-4 FPGA上成功实现,并使用包含英国板块的1000个图像的数据库进行测试。 它消耗了28%可用的片上资源,最大频率为114.20 MHz,检出率为99.1%,并且能够在3.8ms中处理一个图像(640× 480)。

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