X射线图像三维重建的自标定优化算法

根据X射线图像成像特点,提出一种适用于X射线图像三维重建的自标定算法。首先基于SIFT算法得到相邻2幅X射线图像对应轮廓特征匹配关系;然后根据匹配关系计算得到基础矩阵;接着根据基础矩阵估计X射线无损检测设备内参数初值;最后基于改进Kruppa方程优化内参数,得到X射线图像三维重建自标定内参数。根据优化前后的内参数建立的电力金具三维模型,从形状和关键尺寸误差2方面进行对比,结果表明优化后的内参数具有较高的精度和可靠性。

An self-calibration optimization algorithm for 3D reconstruction of X-ray images

According to the imaging characteristics of X-ray images, we propose a self-calibration method for 3D reconstruction of X-ray images. Firstly, the matching relationship of profiles between two adjacent X-ray images is obtained by using the SIFT algorithm. Then, the fundamental matrix is achieved by calculation according to the matching relationship. Thirdly, the initial values of the intrinsic parameters of the X-ray non-destructive testing equipment are estimated by using the fundamental matrix. Finally, the intrinsic parameters are optimized based on the improved Kruppa equation, and the intrinsic self-calibration parameters of the 3D reconstruction of the X-ray image are obtained. According to the intrinsic parameters before and after optimization, the 3D models are established. Comparative experiments are carried out from two aspects: shape and key dimension error, which proves that the optimized intrinsic parameters have higher precision and reliability.