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Automatic Recognition of Road Signs

机译:自动识别道路标志

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摘要

The increase in traffic accidents is becoming a serious social problem with the recent rapid traffic increase. In many cases, the driver's carelessness is the primary factor of traffic accidents, and the driver assistance system is demanded for supporting driver's safety. In this research, we propose the new method of automatic detection and recognition of road signs by image processing. The purpose of this research is to prevent accidents caused by driver's carelessness, and call attention to a driver when the driver violates traffic a regulation. In this research, high accuracy and the efficient sign detecting method are realized by removing unnecessary information except for a road sign from an image, and detect a road sign using shape features. At first, the color information that is not used in road signs is removed from an image. Next, edges except for circular and triangle ones are removed to choose sign shape. In the recognition process, normalized cross correlation operation is carried out to the two-dimensional differentiation pattern of a sign, and the accurate and efficient method for detecting the road sign is realized. Moreover, the real-time operation in a software base was realized by holding down calculation cost, maintaining highly precise sign detection and recognition. Specifically, it becomes specifically possible to process by 0.1 sec(s)/frame using a general-purpose PC (CPU: Pentium4 1.7GHz). As a result of in-vehicle experimentation, our system could process on real time and has confirmed that detection and recognition of a sign could be performed correctly.
机译:交通事故的增加正在成为近期交通量迅速增加的严重社会问题。在许多情况下,驾驶员的疏忽是交通事故的主要因素,驾驶员援助系统要求支持驾驶员的安全。在这项研究中,我们通过图像处理提出了新的自动检测和识别道路标志的方法。本研究的目的是防止驾驶员的疏忽引起的事故,并在驾驶员违反交通规局时对驾驶员提请注意。在该研究中,通过从图像中移除路标除了路标之外,实现高精度和高效的符号检测方法,并使用形状特征检测道路标志。首先,从图像中删除了路标中未使用的颜色信息。接下来,删除除圆形和三角形的边缘以选择标志形状。在识别过程中,对标志的二维分化模式进行了归一化的互相关操作,实现了检测道路标志的准确和有效的方法。此外,通过按住计算成本,实现了高精度的符号检测和识别,实现了软件基础中的实时操作。具体地,具体地使用通用PC(CPU:Pentium4 1.7GHz)来处理0.1秒/框架。由于车载实验,我们的系统可以实时处理,并确认可以正确地执行标志的检测和识别。

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