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An improved vehicle panoramic image generation algorithm

机译:一种改进的车辆全景图像生成算法

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摘要

In order to reduce the traffic accidents caused by the blind area, vehicle panoramic view system has been paid more and more attention. However, the panoramic system is a complex and difficult system. In this paper, we propose an improved vehicle panoramic image generation algorithm. Several key technologies have been improved to ensure reliability and efficiency. First of all, we improve the spherical perspective projection algorithm (SPP) based on the scanning line idea and bilinear interpolation to rectification the fisheye image. Then the inverse perspective projection mapping of undistorted image is used to obtain a top view. In order to reduce computation, the method of manually selecting the target point is carried out. Finally, SURF algorithm is used to find the feature points between the bird's-eye view images around vehicle. We further put forward to utilize a RANSAC algorithm based on block matching to eliminate the mismatched points in the key point matching process. Experimental results indicate that our vehicle panoramic image generation method works efficiently. The proposed algorithm can effectively remove the serious distortion of fisheye lens, and generate a panoramic image around the vehicle in the end. It possesses good robustness, and can be widely used.
机译:为了减少由盲区引起的交通事故,车辆全景系统越来越受到重视。但是,全景系统是一个复杂而困难的系统。在本文中,我们提出了一种改进的车辆全景图像生成算法。已改进了几项关键技术,以确保可靠性和效率。首先,我们基于扫描线思想和双线性插值改进了球面透视投影算法(SPP),以校正鱼眼图像。然后,使用未变形图像的反透视投影映射来获得顶视图。为了减少计算,执行了手动选择目标点的方法。最后,使用SURF算法在车辆周围的鸟瞰图图像之间找到特征点。我们进一步提出利用基于块匹配的RANSAC算法来消除关键点匹配过程中的不匹配点。实验结果表明我们的车辆全景图像生成方法有效地工作。该算法可以有效消除鱼眼镜头的严重畸变,并最终生成车辆周围的全景图像。它具有良好的鲁棒性,可以广泛使用。

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