## 1 Introduction  
The Internet of Things (IoT) is an important part of the new generation of information technology. As the name suggests, the IoT technology aims to build a set of networks in which each object is connected. The IoT is widely used in network convergence through intelligent sensing, recognition technology, and ubiquitous computing and other communication sensing technologies [1]. The most widely used form of IoT is the quick response code (QR code) of different objects [2]. However, when the QR code is outdoors, especially in dark and distant conditions, the QR code scanning is difficult to implement. This limits the wider application of 2-D code access technology. Therefore, the market is in urgent need of access technology that can meet the specific environmental needs. The visible light communication (VLC) becomes the preferred technology. A lot of research in the field of VLC has been done in recent years [3; 4; 5; 6; 7]. By modulating the frequency of light-emitting diodes (LEDs) up to several hundred MHz, which is undetectable to the human eyes [8; 9], this is the basis for using VLC as access technology. Furthermore, there are a lot of advantages of VLC. First, the visible part of the electromagnetic spectrum is unlicensed and unregulated, and LEDs are more energy efficient than other radio transmitters [10]. Second, the line of sight (LOS) property ensures secrecy in the process of information transmission [11]. Lastly, it is well known that LEDs have been widely used, so VLC is easy to popularize. It is attractive to make the VLC as a supplement to traditional QR codes due to its advantages. In Ref. [12], a security system that is built using a barcode-based VLC system between smart phones is proposed. The results show that the system achieves a high level of security. However, the transmitter of the system uses LEDs in a smartphone, which leads to uneven light output, and the error rate increases due to the \"blooming\" effect of image sensors caused by uneven light output. In Ref. [13], [PERSON] et al. use LED panel lights to reduce the possibility of overexposure and avoid the blooming effect of the camera. This method achieves good performance in the symbol error rate (SER) test. However, the effective transmission distance is too short (about 4 cm), and when the distance is large, the data packet may be partially lost. In fact, VLC can be divided into two modes: one is photodiode-based (PD-based) and the other is image-sensor based [14; 15; 16]. A PD-based VLC system works by receiving the light intensity of different LEDs. It is low cost but it is not stable. With the interference of the background light or the reflection of the wall, performance would deteriorate. In the VLC system based on an image sensor, the LED projection of the image is taken as the foreground and the ambient light as the background. The image processing method makes it easy to extract the foreground and reduce the interference of ambient light. Therefore, it is different from the method based on PD since ambient light does not directly affect the captured images of the LED projection. In addition, with the popularization of smart phones, VLC based on an image sensor can be conveniently applied. Smartphones generally have cameras with a CMOS sensor but no PD. Therefore, comparing two modes of the VLC system, the image-sensors are more suitable to supplement QR code scanning technology. In our previous work [17], we proposed an LED-ID detection and identification method based on image-sensors-based VLC for indoor visible light positioning (VLP). However, only 1035 unique IDs were implemented under the same brightness condition. This was far from meeting the requirements of the supplementary technique for QR code. Therefore, in this paper, we propose Optical Bar Code (OBC), which is an entirely new VLC system that is different from the traditional 0-1 digital encoding and decoding. We adopted the method of image feature extraction and innovatively used machine learning to build classifiers.