An Adaptive Deblurring Vehicle Detection Method for High-Speed Moving Drones: Resistance to Shake

Abstract

Vehicle detection is an essential part of an intelligent traffic system, which is an important research field in drone application. Because unmanned aerial vehicles (UAVs) are rarely configured with stable camera platforms, aerial images are easily blurred. There is a challenge for detectors to accurately locate vehicles in blurred images in the target detection process. To improve the detection performance of blurred images, an end-to-end adaptive vehicle detection algorithm (DCNet) for drones is proposed in this article. First, the clarity evaluation module is used to determine adaptively whether the input image is a blurred image using improved information entropy. An improved GAN called Drone-GAN is proposed to enhance the vehicle features of blurred images. Extensive experiments were performed, the results of which show that the proposed method can detect both blurred and clear images well in poor environments (complex illumination and occlusion). The detector proposed achieves larger gains compared with SOTA detectors. The proposed method can enhance the vehicle feature details in blurred images effectively and improve the detection accuracy of blurred aerial images, which shows good performance with regard to resistance to shake.

HMD-Net: A Vehicle Hazmat Marker Detection Benchmark

“…Therefore, reducing the accident rate by detecting and monitoring vehicles for hazmat transportation is a common concern for the government, manufacturers and carriers. In fact, there are many ways for vehicle monitoring [2,3]. In terms of vehicles for hazmat transportation, as required by the Standardization Administration of China, they must be installed and attached with corresponding warning markers, including triangle light boxes and license plates, as shown in Figure 1a and Figure 1b, respectively.…”

Adaptive Signal Processing and Machine Learning Using Entropy and Information Theory

“…The sixth paper [ 6 ], titled “An Adaptive Deblurring Vehicle Detection Method for High-Speed Moving Drones: Resistance to Shake”, proposes an improved GAN (generative adversarial networks) called Drone-GAN (which is an end-to-end adaptive vehicle detection algorithm (DCNet) for drones) to enhance the vehicle features of blurred images to be processed for unmanned aerial vehicles (UAVs).…”