基于八邻域和混合二值化技术的车牌识别与字符分割

P. Ramasubramanian, R. Emiliya, R. Janaki, B. Daniel, C. Anand
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引用次数: 2

摘要

车牌识别(NPR)和字符分割(CS)是智能交通系统的重要组成部分。本文提出了一种适用于印度车牌的车牌识别系统。该方法主要包括两个模块:NPR和CS。采用直方图均衡化技术解决图像对比度低、动态范围小的问题,采用八邻技术过滤图像中不需要的区域。在遗传算法中,提出了混合二值化技术来有效分割污物NP中的特征。该系统使用数码相机捕捉车辆在不同背景和条件下的图像。结果是非常可观的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Number plate Recognition and Character Segmentation using Eight-Neighbors and hybrid binarization techniques
Number Plate Recognition (NPR) and Character Segmentation (CS) play a major role in one of the intelligent transportation system. This paper identifies a number plate identification system for Indian plates. This method consists of two main modules: NPR and CS. In NPR, histogram equalization is employed to solve the low contrast and dynamic-range problems and Eight-Neighbors technique is proposed to filter the unwanted areas in the image. In CS, the hybrid binarization technique is proposed to effectively segment the characters in the dirt NP. The system captures the images of the vehicles at various backgrounds and conditions using a digital camera. The results are highly appreciable.
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