Rapid Detection of Multi-QR Codes Based on Multistage Stepwise Discrimination and a Compressed MobileNet

作者：Chen, Rongjun; Huang, Hongxing; Yu, Yongxing; Ren, Jinchang^*; Wang, Peixian; Zhao, Huimin^*; Lu, Xu^*

来源：IEEE Internet of Things Journal, 2023, 10(18): 15966-15979.

DOI：10.1109/JIOT.2023.3268636

• QR codes
• Codes
• Internet of Things
• Image edge detection
• Task analysis
• Image coding
• Terminology
• Embedded edge devices
• Internet of Things (IoT)
• MobileNet
• multi-QR codes
• rapid detection

Poor real-time performance in multi-QR codes detection has been a bottleneck in QR code decoding-based Internet of Things (IoT) systems. To tackle this issue, we propose in this article a rapid detection approach, which consists of multistage stepwise discrimination (MSD) and a Compressed MobileNet. Inspired by the object category determination analysis, the preprocessed QR codes are extracted accurately on a small scale using the MSD. Guided by the small scale of the image and the end-to-end detection model, we obtain a lightweight Compressed MobileNet in a deep weight compression manner to realize rapid inference of multi-QR codes. The average detection precision (ADP), multiple box rate (MBR) and running time are used for quantitative evaluation of the efficacy and efficiency. Compared with a few state-of-the-art methods, our approach has higher detection performance in rapid and accurate extraction of all the QR codes. The approach is conducive to embedded implementation in edge devices along with a bit of overhead computation to further benefit a wide range of real-time IoT applications.

• 单位
  广东技术师范学院