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Robust vehicle detection and tracking method for Blind Spot Detection System by using vision sensors

机译:使用视觉传感器的盲点检测系统鲁棒车辆检测和跟踪方法

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This paper presents a method to detect the present vehicles from side and rear for BSDS(Blind Spot Detection System) with vision system. Because the real image acquired during car driving has a lot of information to exam the target vehicle, background image, and the noises such as lighting and shading, it is hard to extract only the target vehicle for the background image with satisfied robustness. In this paper, the target vehicle is detected by repetitive image processing such as sobel and morphological operations and a Kalman filter is also designed to cancel the background image and prevent the misreading of the target image. Compared to previous researches, the proposed method can get an image processing with much improved speed and robustness. Various experiments were performed on the highway driving situations to evaluate the performance of the proposed algorithm.
机译:本文介绍了一种用视觉系统检测来自侧面和后部的当前车辆的方法。因为在汽车行驶期间获得的真实图像具有大量信息来检查目标车辆,背景图像和诸如照明和阴影的噪声,因此很难仅提取用于背景图像的目标车辆,满意的鲁棒性。在本文中,通过诸如Sobel和形态学操作的重复图像处理来检测目标车辆,并且Kalman滤波器也被设计成消除背景图像并防止目标图像的误读。与以前的研究相比,所提出的方法可以获得具有大大提高速度和稳健性的图像处理。在公路驾驶情况下进行各种实验,以评估所提出的算法的性能。

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