Recognizing Persian license plates in digital zoom condition

Elham Kordi Ghasrodashti, M. Yazdi
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引用次数: 1

Abstract

In this paper, we propose an algorithm of license plates recognition from their images captured by a camera in digital zoom using a binary time delay neural network (TDNN). Moreover, hard conditions such as the distance and angle variations as well as weather and light conditions are considered. For training the neural network, we collected the training images using the Zernike moment when the camera was not in the magnification state and the test images when the camera was in zooming state. The comparison was made between the proposed algorithm and the previous methods in character recognition like SVM and classical TDNN. The algorithms have been evaluated using 50 license plate images with magnification of 8. The recognition rate obtained by the proposed algorithm was 70%.
识别数字变焦状态下的波斯车牌
本文提出了一种基于二进制延时神经网络(TDNN)的数字变焦相机车牌图像识别算法。此外,还考虑了距离和角度变化以及天气和光照条件等恶劣条件。为了训练神经网络,我们使用相机非放大状态下的泽尼克矩采集训练图像,使用相机变焦状态下的测试图像。将该算法与SVM、经典TDNN等字符识别方法进行了比较。使用50张放大倍数为8的车牌图像对算法进行了评估。该算法的识别率为70%。
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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