In this paper, we propose a weight calculation method to solve a problem of Multiscale Normalized Cut (MNCut) image segmentation. Since Multiscale is incorporated with various information, robust segmentation results can be expected for various RGB images. However, MNCut has a problem that if the foreground or background is separated into two or more regions, they may be classified into different labels. To solve this problem, we use Matting Laplacian2 for edge weight calculation. In the experimental results, the proposed method obtained the results closer to the ground truth.
We propose a new method for measuring three-dimensional (3D) estimation distribution in water around a heat source. By using near infrared (NIR) light, it is possible to measure the total amount of temperature on the optical path. The total amount of temperature obtained is converted into local temperature distribution based on certain assumption. The conventional method estimates temperature distribution using symmetric inverse Abel transformation based on the strong constraint that heat propagates axially symmetrically from the axis passing through the center of the heat source upward. There are two points to be improved in the conventional method. The first point to be improved is that the temperature is assumed to be distributed circularly symmetrically from the axis passing through the heat source center. In fact, in many cases, heat propagates asymmetrically. In this case, the conventional method cannot obtain accurate results. In this paper, we use asymmetric inverse Abel transformation instead symmetric inverse Abel transformation in order to perform asymmetric estimation. The second point to be improved is that the conventional method does not take into consideration that heat propagates smoothly. In this paper, we use an optimization algorithm to smooth adjacent surfaces of the temperature distribution. Experiment showed that the proposed method estimated temperature distribution more accurately than the conventional method.