RESUMO
We propose a descattering method that can be easily applied to food production lines. The system consists of several sets of linear image sensors and linear light sources slanted at different angles. The images captured by these sensors are partially clear along the direction perpendicular to the sensors. We computationally integrate these images on the frequency domain into a single clear image. The effectiveness of the proposed method is assessed by simulation and real-world experiments. The results show that our method recovers clear images. We demonstrate the applicability of the proposed method to a real production line by a prototype system.
RESUMO
We propose a time-of-flight measurement algorithm for depth and intensity that is robust to fog. The key idea of the algorithm is to compensate for the scattering effects of fog by using multiple time-gating and assigning one time-gated exposure for scattering property estimation. Once the property is estimated, the depth and intensity can be reconstructed from the rest of the exposures via a physics-based model. Several experiments with artificial fog show that our method can measure depth and intensity irrespective of the traits of the fog. We also confirm the effectiveness of our method in real fog through an outdoor experiment.
RESUMO
We present a framework for optical tomography based on a path integral. Instead of directly solving the radiative transport equations, which have been widely used in optical tomography, we use a path integral that has been developed for rendering participating media based on the volume rendering equation in computer graphics. For a discretized two-dimensional layered grid, we develop an algorithm to estimate the extinction coefficients of each voxel with an interior point method. Numerical simulation results are shown to demonstrate that the proposed method works well.