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Range image recognition based on Bayesian decision rule

机译:基于贝叶斯决策规则的距离图像识别

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摘要

Laser radar is able to simultaneously produce intensity image and 3D range image which provide rich geometric information for object recognition. However, back scatter noise hinders its usage for most laser radars. Range gated imaging laser radar, which can restrain back scatter noise effectively, becomes an emerging research trend. Its specific imaging system makes the recognition method of range gated imagery different from that of other laser radars. In this paper, a new recognition approach is proposed. We represent range image by a series of range slices so that the shape-matching problem is transformed into similarity measure between 2D slices. The correlation coefficient is used to measure the similarity between 2D range slices. The final decision is made by Bayesian decision rule. Experiments demonstrate that the proposed approach is efficient in object recognition of range-gated imaging laser radar. It can handle partial occlusion and noise with high recognition rate as well.
机译:激光雷达能够同时生成强度图像和3D范围图像,这些图像提供了丰富的几何信息以用于对象识别。但是,反向散射噪声阻碍了其在大多数激光雷达中的使用。能够有效抑制后向散射噪声的测距门成像激光雷达成为一种新兴的研究趋势。其特定的成像系统使距离选通图像的识别方法不同于其他激光雷达。本文提出了一种新的识别方法。我们通过一系列距离切片来表示距离图像,以便将形状匹配问题转换为2D切片之间的相似性度量。相关系数用于测量2D范围切片之间的相似性。最终决定由贝叶斯决定规则决定。实验表明,该方法在距离门成像激光雷达的目标识别中是有效的。它也可以以较高的识别率处理部分遮挡和噪声。

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