A 0.2-Terahertz Ceramic Relic Detection System Based on Iterative Threshold Filtering Imaging and Neural Network

Ceramic cultural relics have an important cultural value, and their detection technology plays a pivotal role in the protection of cultural relics. The traditional detection method of ceramic relics is based on X-ray technology, resulting in damage to the cultural relics. The terahertz-wave transmission is nondestructive; yet, the terahertz imaging has several technical problems, such as complex algorithms and unclear imaging. In this paper, we propose a terahertz-wave imaging system of a 0.2-terahertz operating frequency with a single input and single output and perform the transmission imaging experiment of the ceramic container. This design adopts the iterative threshold segmentation imaging method to obtain the high-quality transmission image and the neural network algorithm in the imaging recognition. Both the imaging and identification results effectively prove excellent performance, such as the high efficiency, high precision, and good reliability of the nondestructive testing system for the ceramic relics. The resolution can reach 2 mm, and the time for imaging identification can be