HE‐DETR‐DC5 method to rapidly detect objects on passive THz images in human safety inspection

Abstract

As worldwide counterterrorism operations grow, screening people for concealed objects in public places utilizing Terahertz security technology is becoming increasingly critical. In this letter, a passive THz Human security image Intelligent detection method (HE-DETR-DC5) is proposed that combines histogram equalization (HE) processing and DEtection TRansformer (DETR). The proposed method first performs histogram equalization on passive THz images to improve image contrast. In addition, the cavity convolution is added to the ResNet-50 backbone network to enhance the model's attention to the concealed object in the passive THz image and improve the accuracy. The corresponding model is called DETR-DC5. The experimental results show that the average precision mAP of the proposed method can achieve 99.9%. At the same time, compared to other image enhancement methods, the histogram equalization method used in this letter has better performance and higher detection accuracy. The detection speed of the proposed method is about 0.5 FPS, which can meet the demand for real-time detection. Therefore, the proposed model can efficiently and automatically detect hidden objects in passive THz human security images.