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The Matching Method for Rectified Stereo Images Based on Minimal Element Distance and RGB Component Analysis

机译:基于最小元素距离和RGB分量分析的校正立体图像匹配方法

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A common problem occurring in medical practice is the localization of veins and arteries. To determine the location of these elements, it is not necessary to have a complete 3D model. A much better solution is preliminary segmentation yielding the contour of veins, and further search for stereo correspondence already in binary images. The computational complexity of this approach is much smaller, which guarantees its fast operation. The disparity matrix is created according to the principle that the most likely correct distance between the same elements in the left and right images is the minimum value. Then, the adjacent RGB components surrounding the elements aspiring to be homologous are analysed. The operation of the method is illustrated on the basis of the authors' own images as well as standardized images. In addition, its operation was compared with three recognized and widely used algorithms for image matching. The effectiveness of the new method reaches less than 94 % of correctly matched pixels with a standard deviation of 1.5 pixels and operation time of 90 ms.
机译:在医学实践中发生的常见问题是静脉和动脉的定位。要确定这些元素的位置,不必具有完整的3D模型。更好的解决方案是产生静脉轮廓的初步分割,并进一步在二进制图像中搜索立体对应。这种方法的计算复杂度要小得多,从而保证了其快速运行。视差矩阵是根据以下原理创建的:左右图像中相同元素之间最可能的正确距离是最小值。然后,分析围绕着想要同源的元素的相邻RGB分量。基于作者自己的图像以及标准化图像来说明该方法的操作。此外,将其操作与三种公认且广泛使用的图像匹配算法进行了比较。新方法的有效性达不到正确匹配像素的94%,标准偏差为1.5像素,操作时间为90毫秒。

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