Moving Quick Response Codes Identification: System Performance Analysis and Maximization by Optimization of Illuminance and Exposure Time

Abstract

We studied the relationship of Quick Response (QR) code identification system performances with illuminance on the QR code, exposure time of the camera, and relative moving speed. We studied the root causes of low identification performance problems on moving QR code as well. A physical experiment method study on a minimal working example of a real-time moving QR codes identification system with ZBar QR codes identification algorithm has done, and then the results were quantitatively and qualitatively analyzed. The values of illuminance on the QR code, exposure time of the camera, and relative moving speed used in the experiments were 140 lux - 640 lux, 0.7 ms - 22.2 ms, and 0 m/s - 2.5 m/s, respectively. Our data boundaries of the experiment results regarding exposure and motion blur (mediator variables) were respectively 0.108 lux·s - 12.476 lux·s and 0.0 pixel - 30.4 pixel. We identified physical phenomena in imaging, exposure and motion blur, could make the QR code image too dark/too bright and motion blurred. Such phenomena could make the QR code hard to identify and being the root cause of the problems. Our quantitative study proved that identification system performance is affected by illuminance, exposure time, and relative moving speed. Finally, we proposed a novel solution to overcome the problems by using a numerical method to compute the optimal illuminance on the QR code and the camera's exposure time for the given relative moving speed of the system.