<i>Development of a 3D Multispectral Imaging System using Structured Light</i>

Abstract

Abstract. Typical spectral images are two-dimensional (2D), which is inadequate for imaging three-dimensional (3D) objects such as plants, fruits and vegetables. This paper presents a method of developing a 3D multispectral imaging system using structured light. In addition to retrieving depth information from the objects, 3D reconstruction using structured light can also enhance surface resolution. The 3D multispectral imaging system was established using a RGB industrial camera, a Digital Light Processing projector, and a multispectral camera. The grey code was used for the structured light because of its simplicity and robustness. The RGB camera and the projector were used for 3D reconstruction after being calibrated as a stereo vision system. The multispectral camera was used to obtain multispectral information. In order to map multispectral information into a 3D shape, stereo calibration of the RGB camera and the multispectral camera was performed. Results indicated that the accuracy of the reconstructed 3D object in terms of its size was over 99.43% in comparison to the ground truth. The error of mapping the near infrared image to a 3D shape was 4 pixels in the X axis because the principal point calibration error was 5.47% and 6.61% for the RGB camera and multispectral camera, respectively. The 3D multispectral imaging with structured light was successful, and the performance can be further improved with more accurate system calibrations.