基于改进网格运动统计特征的在线三维测量

Online Three-dimension Measurement Based on Improved Grid Motion Statistical Features

为了解决在线三维测量技术中像素匹配耗时长,准确率低等问题,提出了一种基于改进网格运动统计特征的像素匹配算法。该方法只需一帧固定的正弦光栅投影到被测物体上,由摄影系统连续采集五帧物体在相等位移下的变形条纹图,提取出相应的调制度信息,并利用快速旋转不变性特征算法提取图像的特征点匹配对,然后利用改进的网格运动统计特征算法来实现误匹配对的剔除。最后根据在线三维测量中对其精度要求很高的特点,取其出现位移量最多的值以获得一组相移量相等的条纹图,采用等步相移算法重建出在线移动物体的三维形貌。大量实验验证了该方法的可行性和有效性,与传统的在线傅里叶变换轮廓术算法进行对比,所提方法的鲁棒性更高,能够恢复出更高精度的三维面形。

In order to solve the problems of low accuracy and long time of pixel matching in online threedimension(3D)measurement,a pixel matching algorithm based on improved grid motion statistics features is presented.In this method,only one frame of sinusoidal grating is projected onto the measured object,five frames of deformed patterns caused by the moving object with equal displacement are captured by camera,and the corresponding background light field is extracted.Then,the matching pairs of feature points are extracted by fast rotation invariant feature algorithm,and then the mismatching pairs are eliminated by using the improved grid motion statistical feature algorithm.Finally,according to the characteristics of high precision in online 3D measurement,five equivalent phase-shifting deformed patterns are obtained by taking the value of the highest frequency of the statistical displacement,and then the 3D shape of online moving object is reconstructed by using equal step phase-shifting algorithm.Large numbers of experiments verify the effectiveness and feasibility of the proposed method,and compared with the traditional and online FTP algorithm,the proposed method is more robust and can reconstruct the 3D shape with higher accuracy.