基于兴趣区域滤波方法的车牌识别系统

Rajib Ghosh, Suraj Thakre, Prabhat Kumar
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引用次数: 6

摘要

本文实现了一种针对印度车辆的车牌识别系统。为此,我们提出了一种基于“感兴趣区域(ROI)”的滤波方法来定位车牌(NP)出现的候选区域。在本文提出的滤波方法中,通过检测垂直边缘,去除长边缘和静止区域,在NP图像中定位候选区域。最后,从候选区域中分割出NP区域,然后将其传递给光学字符识别(OCR)系统,以识别车牌中存在的字符和数字。该系统的新颖之处在于探索了基于roi的滤波方法,提高了系统的整体性能。该系统已经使用从真实视频序列中提取的各种车辆NP图像进行了测试,这些图像沿着光线、规模和方向的尺寸变化。实验结果表明了该方法的鲁棒性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A vehicle number plate recognition system using region-of-interest based filtering method
In this paper, a vehicle number plate recognition (VNPR) system is implemented for Indian vehicles. For this purpose, we propose a ‘region-of-interest (ROI)’-based filtering method to locate the candidate regions of number plate (NP) occurrence. In the proposed filtering method, candidate regions are located in the NP image by detecting vertical edges, removing long edges and stationary regions. Finally, the NP region is segmented from the candidate regions before passing it to the optical character recognition (OCR) system for recognition of characters and digits present in the number plate. The novelty of the proposed VNPR system lies in exploring the ROI-based filtering method which improves the overall performance of the proposed VNPR system. The proposed system has been tested using various NP images of vehicles extracted from real-life video sequences that vary along the dimensions of light, scale and orientation. The experimental results demonstrate the robustness of the proposed method.
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