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A Miniature Binocular Endoscope with Local Feature Matching and Stereo Matching for 3D Measurement and 3D Reconstruction

机译:具有局部特征匹配和立体匹配的微型双目内窥镜用于3D测量和3D重构

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摘要

As the traditional single camera endoscope can only provide clear images without 3D measurement and 3D reconstruction, a miniature binocular endoscope based on the principle of binocular stereoscopic vision to implement 3D measurement and 3D reconstruction in tight and restricted spaces is presented. In order to realize the exact matching of points of interest in the left and right images, a novel construction method of the weighted orthogonal-symmetric local binary pattern (WOS-LBP) descriptor is presented. Then a stereo matching algorithm based on Gaussian-weighted AD-Census transform and improved cross-based adaptive regions is studied to realize 3D reconstruction for real scenes. In the algorithm, we adjust determination criterions of adaptive regions for edge and discontinuous areas in particular and as well extract mismatched pixels caused by occlusion through image entropy and region-growing algorithm. This paper develops a binocular endoscope with an external diameter of 3.17 mm and the above algorithms are applied in it. The endoscope contains two CMOS cameras and four fiber optics for illumination. Three conclusions are drawn from experiments: (1) the proposed descriptor has good rotation invariance, distinctiveness and robustness to light change as well as noises; (2) the proposed stereo matching algorithm has a mean relative error of 8.48% for Middlebury standard pairs of images and compared with several classical stereo matching algorithms, our algorithm performs better in edge and discontinuous areas; (3) the mean relative error of length measurement is 3.22%, and the endoscope can be utilized to measure and reconstruct real scenes effectively.
机译:由于传统的单相机内窥镜只能提供清晰的图像而无法进行3D测量和3D重建,因此提出了一种基于双目立体视觉原理的微型双目内窥镜,可以在狭窄和受限的空间中实现3D测量和3D重建。为了实现左右图像中兴趣点的精确匹配,提出了一种新的加权正交对称局部二进制模式(WOS-LBP)描述符的构造方法。然后研究了基于高斯加权AD-普查变换和改进的基于交叉的自适应区域的立体匹配算法,以实现真实场景的3D重建。在该算法中,我们调整了边缘和不连续区域的自适应区域的确定标准,并通过图像熵和区域增长算法提取了由于遮挡而导致的像素不匹配。本文开发了一种外径为3.17mm的双目内窥镜,并应用了上述算法。内窥镜包含两个CMOS摄像头和四个用于照明的光纤。从实验中得出三个结论:(1)所提出的描述符具有良好的旋转不变性,对光变化以及噪声的鲁棒性和鲁棒性; (2)提出的立体匹配算法对Middlebury标准图像对的平均相对误差为8.48%,与几种经典的立体匹配算法相比,我们的算法在边缘和不连续区域中表现更好; (3)测长的平均相对误差为3.22%,可以利用内窥镜有效地测量和重建真实场景。

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