Radiation Scene Reconstruction Based on Image Fusion from Gamma Camera and RGB-D Camera

Abstract

In nuclear measurement, radiation area reconstruction is a hot topic. To reconstruct a radiation environment, we proposed an information fusion method based on images from a gamma camera and an RGB-D (Red Green Blue-Depth) camera. First, on a mobile base, the reconstruction platform is presented to integrate gamma imaging with RGB-D information. Secondly, the dense point cloud map of the environment is formatted with VSLAM (Visual Simultaneous Localization and Mapping) based on an RGB-D camera. Thirdly, from the gamma camera images, the radioactive contour feature is extracted to localize the source right ahead cameras, and the radiation area point cloud is obtained using the relative position of the two cameras. Lastly, the whole radiation environment map is generated with point cloud fusion, and the source position is estimated with the minimum bounding box. To validate the efficiency of this method, a laboratory room with one 152Eu source is reconstructed under above fusion platform. In the experiments, three feature objects are selected, and their size are calculated based on the cloud point. Also, in two scenes with the same size in released literature, the sources are localized. Although there exist some errors, comparisons show that this method performs well and keeps at low deviation level.