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Linear Protection Grid Optimized Image Stitching for Mobile Robots

机译:用于移动机器人的线性保护网格优化图像拼接

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Image stitching can be used to in 3D reconstruction to obtain the comprehensive obstacle information, which plays an important role in the field of mobile robots. However, previous algorithms have two problems: 1. The linear structure of the image might have been corrupted. 2. Some inconsistency may exist in the transitional region of the stitched image. In order to solve above problems, in this paper, we propose a grid-based linear structure protection method, which applies the constraints to the lines extracted from the image to protect them from the distortion caused by the mesh deformation process, and resulting in a natural panorama with reduced distortion. This method helps to obtain a natural panoramic image with reduced distortion. At the same time, we use the neighbor weighted based boundary artifact removal approach to process the stitched image, which can avoid the stitching problem and can make the image look more natural. We conducted some experiments, and the results demonstrated that our method is more efficient and more natural as compared with some state-of-the-art methods.
机译:图像拼接可用于3D重建以获得综合障碍信息,这在移动机器人领域起着重要作用。但是,以前的算法有两个问题:1。图像的线性结构可能已损坏。在缝合图像的过渡区域中可能存在一些不一致。为了解决上述问题,在本文中,我们提出了一种基于网格的线性结构的保护方法,它适用于约束以从图像中提取以保护它们免受引起的网格变形过程中的失真的行,并导致天然全景,减少扭曲。该方法有助于获得具有减小的自然全景图像。同时,我们使用基于邻控的边界工件去除方法来处理缝合图像,这可以避免拼接问题并且可以使图像看起来更自然。我们进行了一些实验,结果表明,与一些最先进的方法相比,我们的方法更加有效,更自然。

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