In the modern world optical sensor systems have a vast number of applications. In this research work the system composed of the two cameras and the laser illumination with the 49 lasers is considered. In the previous research work we proposed the general calibration technique for this system. It was shown that the most complicated subtask in this technique is determining the beam directions for the laser illumination calibration because it couldn’t be solved using the known algorithms. The main stages which are required to execute for determining the beam directions for the laser illumination are: tracking of the laser illumination points in the image sequence of the calibration object; calculation of the coordinates in space for the found laser illumination points; constructing the laser beams in space passing close as much as possible to the found points. Within the scope of the research carried out, all the main stages for determining the beam directions for the laser illumination are considered. But much attention in this work is devoted to the third stage. The origin of the laser beam is known since it coincides with the known location of the laser on the laser illumination. Thus the problem is to find the ray passing through the origin and the least divergent in mean square from the found set of points. Also the algorithms for performing each stage are suggested. Particularly, we developed our own algorithms taking into consideration specifics of the available system with the laser illumination, viz. the algorithms for detecting the laser illumination points, the algorithms for constructing the laser beam from the found set of points. The beam directions in space can be determined for each laser of the illumination. These determined directions can be used as the subset of the calibration parameters for the whole system.
Proc. SPIE. 10332, Videometrics, Range Imaging, and Applications XIV
KEYWORDS: Mathematical modeling, Visual process modeling, Data modeling, LIDAR, Sensors, Computing systems, 3D modeling, Ray tracing, Distance measurement, 3D metrology, Optical simulations, Acousto-optics, Statistical modeling, Atmospheric modeling, Systems modeling, Process modeling, OpenGL
The article considers modeling method of RAW data received by Lidar in real time as well as its implementation. As the method to determine ranging we consider ray tracing method and the alternative method to determine the ranging using Z-buffer which is often applied while 3D modeling. Mathematical apparatus to estimate the power of reflected radiation is offered. The results of the work show the estimation of the performance to implement the offered method on CPU and GPU performed with the help of OpenGL technology.
Applications of computer vision techniques assume an image acquisition from one or another sensing system. This system should be calibrated before the usage to obtain proper results. In this paper a calibration technique for the stereo camera system with the laser illumination is proposed. Modern approaches to the calibration of the different sensing systems are indicated. The characteristics of the specific system required a calibration are described. The main calibration tasks and subtasks for the given system and also the main stages of the proposed technique are highlighted. The need to rotate the laser illumination relative to the axis between the cameras through 8 degrees is proven. An approach to the calibration of the illumination laser beam directions is developed. The accounting of the parameters which can be obtained as an issue of the complex calibration of the stereo camera system with the laser illumination makes it possible to improve the results of the analyzed system utilization for mobile robots.
Epoxy resins have wide applications in modern industries. To improve the properties of such resins the thermoplastic component is often used. This component dissolves in the epoxy resin at a high temperature. To determine the properties of the obtained cured epoxy matrix with thermoplastic particles it is important to estimate and classify this particle sizes. In this paper we investigate methods for solving these tasks automatically. The thermoplastic particle sizes are analyzed using the microscopy images of the cured epoxy matrix. The digital image processing methods for the thermoplastic particle detection are discussed. The Otsu’s method is implemented for microscopic images with homogeneous background. The Circular Hough Transform method is implemented for microscopic images with big visible particle radii. The results of both methods for the considered images are represented. The parameters of the Gaussian distribution for the thermoplastic particle sizes in a cured epoxy matrix are estimated from the analyzed microscopic images.