OCR-based neural network for ANPR

X. Zhai, F. Bensaali, R. Sotudeh
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引用次数: 54

Abstract

Optical Character Recognition (OCR) is the last stage in an Automatic Number Plate Recognition System (ANPRs). In this stage the number plate characters on the number plate image are converted into encoded texts. In this paper, an Artificial Neural Network (ANN) based OCR algorithm for ANPR application is presented. A database of 3700 UK binary character images have been used for testing the performance of the proposed algorithm. Results achieved have shown that the proposed algorithm can meet the real-time requirement of an ANPR system and can averagely process a character image in 8.4ms with 97.3% successful recognition rate.
基于ocr的ANPR神经网络
光学字符识别(OCR)是车牌自动识别系统的最后一个环节。在这个阶段,车牌图像上的车牌字符被转换成编码文本。本文提出了一种基于人工神经网络(ANN)的OCR算法。3700个英国二进制字符图像的数据库已被用于测试所提出的算法的性能。实验结果表明,该算法能够满足ANPR系统的实时性要求,平均在8.4ms内处理一幅字符图像,识别率为97.3%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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