MVSR Normalization Algorithm Method for Improving Vehicle License Plate Recognition

Sertaç Yaman, Yavuz Erol
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Abstract

Image processing and embedded systems are used in many applications such as object recognition, robotic applications, autonomous and remote control systems developed for the defense industry, medical applications, face recognition, and vehicle license plate recognition. Many vehicle license number plate detection methods are not effective under vehicle license plate images have a degree of rotation or low resolution images. Thus, we used MVSR normalization algorithm to detect vehicle license plate recognition for better accuracy and lower computational cost. The MVSR normalization algorithm, Mean–Variance-Softmax-Rescale processes respectively is applied for high-accuracy real-time vehicle license plate detection.
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改进车牌识别的MVSR归一化算法
图像处理和嵌入式系统用于许多应用,例如物体识别、机器人应用、为国防工业开发的自主和远程控制系统、医疗应用、人脸识别和车辆牌照识别。许多机动车号牌检测方法在机动车号牌图像有一定程度旋转或分辨率较低的情况下效果不佳。因此,我们使用MVSR归一化算法来检测车牌识别,具有更高的准确率和更低的计算成本。将MVSR归一化算法、Mean-Variance-Softmax-Rescale过程分别应用于车牌的高精度实时检测。
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