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Color Feature and Density Based Image Mosaicing Using Repeated Application of the ICP Algorithm

机译:使用ICP算法重复应用的彩色特征和基于密度的图像镶嵌

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A Color Feature and Density based (CFD) image mosaicing (IM) algorithm is presented in this paper. In the initial step, color image segmentation is used to provide a global match between an image pair. The well-known Iterated Closest Point (ICP) algorithm is used to find a transformation for global alignment. Finally, the ICP algorithm is applied again to find a transformation for local adjustment. By using this approach, it is shown that we can guarantee global alignment accuracy because the feature based method is used to find the initial matching of two image frames. We achieve local optimal pixel alignment based on the minimization of the Sum of Squares of Differences (SSD) between two images from the same overlapping area.
机译:本文提出了一种彩色特征和基于密度(CFD)图像镶嵌(IM)算法。在初始步骤中,彩色图像分割用于提供图像对之间的全局匹配。众所周知的迭代最接近点(ICP)算法用于找到全局对齐的转换。最后,再次应用ICP算法以找到用于本地调整的转换。通过使用这种方法,表明我们可以保证全局对准精度,因为基于特征的方法用于找到两个图像帧的初始匹配。我们基于来自相同重叠区域的两个图像之间的差异(SSD)的总和的最小化实现局部最佳像素对齐。

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