The detection and recognition of RGB-LED-ID based on visible light communication using convolutional neural network

Abstract

In this paper, an online to offline (O2O) method based on visible light communication (VLC) is proposed, which is different from the traditional VLC with modulation and demodulation. It is a new VLC with modulation and recognition. We use RGB light emitting diode (RGB-LED) as the transmitter, and use Pulse Width Modulation (PWM) to modulate the signal to make it flicker at high frequency. Therefore, several features are created. At the receiver, the complementary metal-oxide-semiconductor (CMOS) image sensor is applied to our system to capture LED images with stripes. A convolution neural network (CNN) is then introduced in our system as a classifier. By offline training for the classifiers and online recognition of LED-ID, the scheme proposed could improve the speed of LED-ID (the unique identification of each different LED) identification and improve the robustness of the system. This is the first application of CNN in the field of VLC.