The registration of point cloud is important for large object measurement. A measurement method for coordinate system transformation based on robot is proposed in this paper. Firstly, for obtaining extrinsic parameters, the robot moves to three different positions to capture the images of three targets. Then the transformation matrix X between camera and tool center point (TCP) coordinate systems can be calculated by using the known parameters of robot and the extrinsic parameters, and finally the multi-view coordinate system can be transformed into robot coordinate system by the transformation matrix X. With the help of robot, the multi-view point cloud can be easily transformed into a unified coordinate system. By using robot, the measurement doesn’t need any mark. Experimental results show that the method is effective.

In order to realize the online measurement of lamp dimension, the bulb image dimension measurement based on vision (BIDMV) is proposed. The image of lamp is obtained by camera. After image processing, such as Otsu algorithm, median filter, ellipse fitting and envelope rectangle fitting, the dimension of lamp can be calculated. Based on this method, a non-contact real-time measurement system of the lamp’s dimension is developed. The precision of the proposed method is 0.07 mm, and it can satisfy the tolerance of the National Standard GB15766.1-2008. The experiment results show that the proposed method has a faster measuring speed and a higher precision compared with other measurement methods.

For fabric defect identification in the textile industry, a three-dimensional (3D) color phase shift profilometry (CPSP) method is proposed. The detecting system is mainly composed of one CCD camera and one digital-light-processing (DLP) projector. Before detection, the system should be calibrated to make sure the camera parameters. The CPSP color grating is projected to the measured fabric by DLP projector, and then it is collected by CCD camera to obtain the grating phase. The 3D measurement can be completed by the grating phase difference. In image acquisition, only invariable grating is projected to the object. In order to eliminate the interference from background light during the image acquisition, the brightness correction method is researched for improving the detection accuracy. The experimental results show that the false rate of detecting the fabric defects is 5.78%, the correct rates of detecting the fabric defects of hole and qualified fabric are both 100%, and the correct rates of detecting the fabric defect of scratch and fold are 98% and 96%, respectively. The experiment proves that the proposed method can accurately identify fabric defects.