A new approach for three dimensional (3-D) shape measurement was proposed based on colorcoded fringe and neural networks. By applying the phase-shift technique to fringe projection, point clouds were generated with hi...A new approach for three dimensional (3-D) shape measurement was proposed based on colorcoded fringe and neural networks. By applying the phase-shift technique to fringe projection, point clouds were generated with high spatial resolution and limited accuracy. The picture element correspondence problem was solved by using projected color-coded fringes with different orientations. Once the high accurate corresponding points were decided, high precision dense 3-D points cloud was calculated by the well trained net. High spatial resolution can be obtained by the phase-shift technique and high accuracy 3-D object point coordinates are achieved by the well trained net, which is not dependent on the camera model and will work for any type of camera. Some experiments verify the performance of this method.展开更多
Dithering optimization techniques can be divided into the phase-optimized technique and the intensity-optimized technique. The problem with the former is the poor sensitivity to various defocusing amounts, and the pro...Dithering optimization techniques can be divided into the phase-optimized technique and the intensity-optimized technique. The problem with the former is the poor sensitivity to various defocusing amounts, and the problem with the latter is that it cannot enhance phase quality directly nor efficiently. In this paper, we present a multi-objective optimization framework for three-dimensional(3D) measurement by utilizing binary defocusing technique. Moreover, a binary patch optimization technique is used to solve the time-consuming issue of genetic algorithm. It is demonstrated that the presented technique consistently obtains significant phase performance improvement under various defocusing amounts.展开更多
基金Supported by the Eleventh Five-Year Pre-Research Project of China
文摘A new approach for three dimensional (3-D) shape measurement was proposed based on colorcoded fringe and neural networks. By applying the phase-shift technique to fringe projection, point clouds were generated with high spatial resolution and limited accuracy. The picture element correspondence problem was solved by using projected color-coded fringes with different orientations. Once the high accurate corresponding points were decided, high precision dense 3-D points cloud was calculated by the well trained net. High spatial resolution can be obtained by the phase-shift technique and high accuracy 3-D object point coordinates are achieved by the well trained net, which is not dependent on the camera model and will work for any type of camera. Some experiments verify the performance of this method.
基金Project supported by the Zhejiang Provincial Welfare Technology Applied Research Project,China(Grant No.2017C31080)
文摘Dithering optimization techniques can be divided into the phase-optimized technique and the intensity-optimized technique. The problem with the former is the poor sensitivity to various defocusing amounts, and the problem with the latter is that it cannot enhance phase quality directly nor efficiently. In this paper, we present a multi-objective optimization framework for three-dimensional(3D) measurement by utilizing binary defocusing technique. Moreover, a binary patch optimization technique is used to solve the time-consuming issue of genetic algorithm. It is demonstrated that the presented technique consistently obtains significant phase performance improvement under various defocusing amounts.
