A convenient look-up-table based method for the compensation of non-linear error in digital fringe projection

Although the structured light system that uses digital fringe projection has been widely implemented in three-dimensional surface profile measurement, the measurement system is susceptible to non-linear error. In this work, we propose a convenient look-up-table-based （LUT-based） method to compensate for the non-linear error in captured fringe patterns. Without extra calibration, this LUT-based method completely utilizes the captured fringe pattern by recording the full-field differences. Then, a phase compensation map is established to revise the measured phase. Experimental results demonstrate that this method works effectively.

Measuring the kinematics of a free-flying hawk-moth(Macroglossum stellatarum)by a comb-fringe projection method

We describe a 2D fringe projection method that involves projecting two groups of sharp comb fringes onto a free-flying hawk-moth from different directions and recording the images of distorted fringes by two high speed cameras from two orthogonal views. By calculating the 3D coordinates of the points on the hawk-moth and three-dimensional reconstruction of the wing, the flight trajectory, body attitude and wing kinematics including flapping angle, elevation angle, torsion angle, and camber deformation are obtained.

A study of making use of computer-aided projection fringe system to measure breast dimension

To measure breast basic dimension by using computer-aided projection fringe system.Methods A system has been developed for measuring breast basic dimension based on computer-aided projection fringe measurement and programming software.Plastic manikins breast’s SN-N (sternal notch to nipple distance),N-ML (nipple to midline distance),N-N (internipple distance),MBW (base width of breast) and N-IMF (nipple to inframammary fold distance) are measured with this system.At the same time,these items are also measured with routine ruler.Results This study indicate that the system has some merits:① non-touching measurement;② it is very rapid,the patient measured need hold his breath only 0.5 second,and all the time it takes is about 2.5 minutes;③ the measurement’s sensitivity is as high as to 0.6 mm,which meets the clinic requirement entirely;④ the measurement’s accuracy of the system is not significantly when comparing to the routine ruler’s.Conclusion Computer-adided projection fringe system for measuring breast basic dimension is feasible and advanced.14 refs,1 fig.

MULTIPARAMETER MEASUREMENT FOR RACEWAY GROOVE OF BEARING BASED ON 3D RECONSTRUCTION WITH DIGITAL STRUCTURED LIGHT

A fast 3D reconstruction method based on structured light to measure various parameters of the raceway groove is presented. Digital parallel grating stripes distributed with sine density are projected onto the raceway groove by a DLP projector, and distorting of stripes is happened on the raceway. Simultaneously, aided by three-step phase-shifting approach, three images covered by different stripes are obtained by a high-resolution CCD camera at the same location, thus a more accuracy local topography can be obtained. And then the bearing is rotated on a high precision computer controlled rotational stage. Three images are also obtained as the former step at next planned location triggered by the motor. After one cycle, all images information is combined through the mosaics. As a result, the 3D information of raceway groove can be gained. Not only geometric properties but also surface flaws can be extracted by software. A preliminary hardware system has been built, with which some geometric parameters have been extracted from reconstructed local topography.

Phase unwrapping based on deep learning in light field fringe projection 3D measurement

Phase unwrapping is one of the key roles in fringe projection three-dimensional(3D)measurement technology.We propose a new method to achieve phase unwrapping in camera array light filed fringe projection 3D measurement based on deep learning.A multi-stream convolutional neural network(CNN)is proposed to learn the mapping relationship between camera array light filed wrapped phases and fringe orders of the expected central view,and is used to predict the fringe order to achieve the phase unwrapping.Experiments are performed on the light field fringe projection data generated by the simulated camera array fringe projection measurement system in Blender and by the experimental 3×3 camera array light field fringe projection system.The performance of the proposed network with light field wrapped phases using multiple directions as network input data is studied,and the advantages of phase unwrapping based on deep learning in light filed fringe projection are demonstrated.