Enhancing point cloud data fusion through 2D thermal infrared camera and 2D lidar scanning

Abstract

Abstract

Sensor data fusion from multiple sources plays a pivotal role in advancing our understanding of real-world phenomena. This paper focuses on the integration of a thermal imager and a lidar to simultaneously capture four-dimensional (XYZT) space coordinates and temperatures. The fusion of data relies on establishing correspondence between overlapping lines in the lidar’s 3D point cloud and the infrared (IR) camera’s 2D thermal map. The presented combination method offers several key advantages. Firstly, it simplifies the calibration process. Furthermore, it can achieve near real-time performance, enabling prompt data analysis. Moreover, the method demonstrates high accuracy in capturing spatial information and temperature measurements. The thermal IR camera used in the experiment features a 1280 × 1024 pixel cooled indium antimonide (InSb) detector, operating in the short wavelength infrared (MWIR) spectral range of 1.5 to 5.5 µm. It provides temperature readings with ± 1 K accuracy and sub-30 mK resolution. On the other hand, the lidar system delivers centimeter-level precision within a range of approximately 1 to 12 m, even in well-lit outdoor environments. The experimental results validate the effectiveness of our combined system, successfully generating high-quality four-dimensional (4D) point clouds. The integration of the thermal IR camera and profilometer presents an intriguing tool with significant potential in various industrial applications. For instance, it can be employed to accurately assess gas leaks, enhance metallurgical processes, and improve safety on construction sites.