The LED-ID Detection and Recognition Method Based on Visible Light Positioning Using Proximity Method - Canyu Xie; Weipeng Guan; Yuxiang Wu; Liangtao Fang; Ye Cai (IEEE Photonics Journal)
Complementary metal-oxide-semiconductor (CMOS) sensor based visible light positioning (VLP) has been widely studied in recent years due to its high robustness and high precision. In most researches about CMOS sensor based VLP, researchers always focus on the high-precision positioning algorithm but ignore that the accuracy of LED-ID detection and recognition plays a more important role in a VLP system. Without the correct recognition of LED-ID, the positioning algorithm would be meaningless no matter how effective it is. In addition, high-precision positioning is not required in most applications since it is enough for people to know just the approximate location. To solve these problems, in this paper, an LED-ID detection and recognition method based on visible light positioning using proximity method is propose. Different from the traditional LED-ID coding and decoding method, we create different features for different LED-ID, and use a machine learning method to identify the LED-ID once the feature extraction and selection of the LED image is achieved with an image processing method. It is the first time the machine learning method is used for LED-ID recognition in VLP. Moreover, we use a proximity-based positioning method to get the approximate location since it is easy to obtain once the LED-ID is recognized. The studies we have demonstrated shows that the proposed method can achieve high LED-ID recognition rate, and provide enough unique LED-ID for variable large-scale indoor VLP system. Furthermore, with the development of camera technology, the number of the unique LED-ID and the maximum recognizable distance would increase. Therefore, this scheme may be considered as one of the useful LED-ID detection and recognition method for visible light positioning in the future.