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Study and Implementation of Various Image De-Noising Methods for Traffic Sign Board Recognition

机译：交通标志牌识别中各种图像去噪方法的研究与实现

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The problem of recognizing traffic sign boards in a correct fashion is one of the major challenges since there is an alarming rate of increase in the number of road accidents happening because of incorrect interpretation of traffic sign boards in bad weather conditions. In this paper, a comparative analysis of various noise removal techniques based on calculating different parameters which decide the quality of input roadway symbol like Mean Squared Error (MSE), Peak Signal to Noise Ratio (PSNR) as well as Structural Similarity for measuring Image Quality (SSIM) is being performed and the best technique will be chosen among them which gives minimum Mean Squared Error (MSE) value and maximum Peak Signal to Noise Ratio (PSNR) and Structural Similarity for measuring the Image Quality (SSIM) values. This technique will be quite useful for de-noising a given image which is present in both the testing and the training image databases.
机译：以正确的方式识别交通标志牌的问题是主要的挑战之一，因为由于恶劣天气条件下交通标志牌的错误解释，发生的道路交通事故的数量以惊人的速度增长。本文基于计算不同参数的各种噪声消除技术的比较分析，这些参数决定了输入巷道符号的质量，例如均方误差（MSE），峰值信噪比（PSNR）以及用于测量图像质量的结构相似性（SSIM）正在执行中，将从中选择最佳技术，该技术给出最小均方误差（MSE）值和最大峰值信噪比（PSNR）以及用于测量图像质量（SSIM）值的结构相似性。该技术对于消除测试和训练图像数据库中都存在的给定图像的噪声将非常有用。

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