Adaptively undersampled image processing for fast multiline laser detection

A. Molder, O. Martens, T. Saar, R. Land
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引用次数: 5

Abstract

In many image processing applications one of the main problem is how to create algorithms, which are fast enough to be implemented on embedded (with limited resources) computing platforms, like DM3730 processor based development boards (Beagleboard-XM). One such image processing area is related to laser scanners, which are usually implemented on multi-core high performance personal computers. In this paper an adaptively undersampled image processing method for fast multiline laser detection has been proposed. The combination of adaptive undersampling and multiline laser detection significantly reduces the calculation operations, needed for laser line detections, thus making this method highly suitable for limited embedded platforms. This method has been tested with real multiline laser images on pavement surface, on 4 different computing platforms and the results are presented at the end of the paper.
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快速多线激光检测的自适应欠采样图像处理
在许多图像处理应用程序中,主要问题之一是如何创建足够快的算法,以便在嵌入式(资源有限)计算平台上实现,例如基于DM3730处理器的开发板(Beagleboard-XM)。其中一个这样的图像处理领域与激光扫描仪有关,它通常在多核高性能个人计算机上实现。本文提出了一种用于快速多线激光探测的自适应欠采样图像处理方法。自适应欠采样和多线激光检测的结合大大减少了激光线检测所需的计算操作,因此该方法非常适合于有限的嵌入式平台。在4种不同的计算平台上,用路面上的真实多线激光图像对该方法进行了测试,并给出了结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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