YUAN Ze-hui, LI Shi-zhong
（College of Mechatronic Engineering， North University of China， Taiyuan 030051， China）
Abstract： X-ray image has been widely used in many fields such as medical diagnosis, industrial inspection, and so on. Unfortunately, due to the physical characteristics of X-ray and imaging system, distortion of the projected image will happen, which restrict the application of X-ray image, especially in high accuracy fields. Distortion correction can be performed using algorithms that can be classified as global or local according to the method used, both having specific advantages and disadvantages. In this paper, a new global method based on support vector regression (SVR) machine for distortion correction is proposed. In order to test the presented method, a calibration phantom is specially designed for this purpose. A comparison of the proposed method with the traditional global distortion correction techniques is performed. The experimental results show that the proposed correction method performs better than the traditional global one.
Key words： X-ray image; distortion correction; support vector regression machine
CLD number： TP391.41Document code： A
Article ID： 1674-8042（2015）03-0302-05 doi： 10.3969/j.issn.1674-8042.2015.03.018
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基于支持向量回归机的X射线图像畸变校正研究
袁泽慧， 李世中
（中北大学 机电工程学院， 山西 太原 030051）
摘要： X射线图像已经被广泛的应用于各个领域， 如医学诊断， 工业检测等。 然而， 由于x射线及其成像系统的物理特性， 得到的X图像存在严重畸变， 这极大限制了X射线在一些高精度场合的应用， 因此需对原始的x射线图像进行校正。 所谓图像畸变校正， 就是设法建立畸变图像特征点坐标与理想图像特征点坐标之间的映射模型， 即校正模型， 将畸变的点恢复到原来的位置。 目前常用的畸变校正方法主要分为两类： 全局校正法和局部校正法， 这两种方法都有各自的优缺点。 本文提出了利用支持向量回归机建立校正模型的一种全局校正方法， 并将其与全局多项式模型做比较， 通过比较两种模型的校正图像中特征点分布与理想分布的符合度， 检验所提出算法的效果。 实验结果表明， 提出的算法效果明显好于传统的多项式方法。
关键词： X-射线图像； 畸变校正； 支持向量回归机
引用格式：YUAN Ze-hui, LI Shi-zhong. X-ray image distortion correction based on SVR. Journal of Measurement Science and Instrumentation, 2015, 6(3)： 302-306. ［doi： 10.3969／j.issn.1674-8042.2015.03.018］
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