Camera Exposure Optimization and Image Quality Assessment in Structured Light Measurement
To solve the problem that the exposure cannot be determined accurately in the acquisition process of structured light 3D measurement,we propose a method to solve the optimal exposure time based on the camera response function.The background segmentation of different measured object images is mainly performed by using the Otsu method,and then the camera response function is utilized to solve the relationship between the true pixel value and the exposure time,so as to obtain the optimal exposure time under the ideal pixel mean value.In addition,an image quality evaluation method is constructed by calculating the ratio of overexposed and underexposed pixel points in the image and the normalization of other basic image quality evaluation parameters such as pixel mean value,which is capable to effectively evaluate the measured object images.Experiments are conducted using different exposure times for binocular structured light 3D measurements to compare the number of phase-matched points and key feature measurements in the model reconstruction.The results show that when the optimal exposure time is used to acquire the measured object,the image evaluation values are above 90%,the number of phase-matched points are the highest during the model reconstruction process,and the key features are measured accurately with a maximum measurement error of 0.02 mm compared with other measuring methods.Meanwhile,the quality evaluation results of the measured object image are positively correlated with the number of phase-matched points,which proves the effectiveness of the evaluation method.This study provides a scientific basis for the selection of the exposure in structured light 3D measurement.
measurement and metrologystructured light 3D measurementcamera response functionthreshold segmentationimage quality evaluation method