Light Source Tracking System for A-QL based Display-Camera Communication

Optical camera communication (OCC) can be realized by commercial LEDs or displays as a transmitter and image sensors as a receiver. One of the challenges to enhance the transmission capacity in OCC is a two-dimensional light source with a display at the transmitting side. So far, the optimization of the imaging process and the method of tracking and detecting the light source have not been studied in detail. This paper proposes a dynamic light source detection system based on the A-QL method specified in IEEE 802.15.7 as a transmission symbol format. It employs YOLO, a deep learning-based object detection algorithm, and optimizes the image capture process as a symbol detection system. The proposed system can detect two-dimensional symbols with adjusting its angle and orientation. Its effectiveness and feasibility are demonstrated through an experimental evaluation.