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LED street lamp detection for automotive auto beam detection

机译:用于汽车自动光束检测的LED路灯检测

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摘要

As vehicle population increases, the number of road accidents also increases. Vital problems in transportation such as mobility and safety of transportation considered more, especially in metropolitans and highway. It is because of the reflection or refraction of light from different directions also contributed to this accident. Due from that, the driver could not identify the types of lamps in their environment whether it is street lamp or car lamp from others. When other drivers use the high beam from the opposite direction, will cause the view is blurred and glare. Due to that, many road users can be stuck with unintentional accident. The project of Light Emitter Diode (LED) Street Lamp Detection for Automotive Auto Beam Detection will be developed as addition features of the system to detect LED Street Lamp. Basically, this project is to differentiate between LED Street Lamp andudcar lamp to ignore LED noise when it is combined each other. The main purpose of this project is to enhance the automated high beam detection system using image processing technique in MATLAB, to detect LED street lamp for automated high beam detection and also to detect the vehicle-rear lamp within its proper distance for automated high beam detection. In order to implement this project, it was conducted with computer simulation (MATLAB) by using image processing method. There are two ways to identify the image or visual by its color or shape of the objects. My expected outcome is to develop the Graphical Using Interface (GUI) by taking the night vision images.
机译:随着车辆数量的增加,道路交通事故的数量也会增加。运输中的重要问题,例如交通的机动性和安全性,被考虑的更多,尤其是在大都市和高速公路中。正是由于来自不同方向的光的反射或折射也导致了这次事故。因此,驾驶员无法从其他人识别其环境中的灯的类型,无论是路灯还是汽车灯。当其他驾驶员从相反方向使用远光灯时,会导致视野模糊和眩光。因此,许多道路使用者可能会因意外事故而陷入困境。用于汽车自动光束检测的光发射二极管(LED)路灯检测项目将作为检测LED路灯的系统的附加功能而开发。基本上,该项目是区分LED路灯和 udcar灯,以便在彼此组合时忽略LED噪声。该项目的主要目的是使用MATLAB中的图像处理技术增强自动远光灯检测系统,检测用于自动近光灯检测的LED路灯,并检测在适当距离内的车后灯以进行自动远光灯检测。 。为了实施该项目,它是通过使用图像处理方法与计算机仿真(MATLAB)进行的。有两种方法可以通过对象的颜色或形状来识别图像或视觉。我的预期结果是通过拍摄夜视图像来开发图形化使用界面(GUI)。

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    Nurul Fadzlina Jamin;

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  • 年度 2012
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