## 4 Conclusions  
In this paper, an improved tracking method based on visible light communication using a Cam-Shift algorithm and a Kalman filter is proposed in order to make up for the lack of research on target signal source LED tracking and extraction in the exiting VLC reports. Obtaining the region of signal source is the premise of information demodulation in the receiver, while most studies ignore it or assume that there is no background interference in the received images and only valid data is left in these images. However, this is not the case. In an actual situation, there are other luminous or reflective object interference in images and the transmitter or the receiver can be moving or stationary, meaning the information of the signal source cannot be demodulated directly. Therefore, we proposed an improved algorithm that considered the color characteristics and special distribution characteristics of the target at the same time, converting the original image to a color probability distribution map based on the color histogram of the target and adaptively adjusting the location and size of the search window based on the results obtained from the previous frame. Meanwhile, the motion state of the target signal source LED in the next frame is predicted according to the position and velocity information of the current frame to enhance tracking robustness when interference occurs.  
As the experimental results show, the proposed algorithm possessed high accuracy and its tracking error was 0.85 cm. Furthermore, the average computational time of processing one frame was 0.042 s, meaning it had a good real-time performance. Most important of all, the improved algorithm had good robustness and the practical scenario in an image-sensor based OVLC system was taken into consideration, solving the problem of tracking and extracting the signal source area from images with different interferences, which is the premise of communication under dynamic scenes. Therefore, the proposed algorithm can be used in an image-sensor based VLC system, especially for communication in a motion state, and applied to both indoor and outdoor applications, promoting the feasibility of OVLC application and filling in gaps in this research area.  
\begin{table}
\begin{tabular}{c c} \hline \hline
**LED’s Category of Videos** & **Processing Time of Each Frame (s)** \\ \hline Green signal source LED & 0.042 \\ Blue signal source LED & 0.041 \\ Red signal source LED & 0.041 \\ White signal source LED & 0.043 \\ \hline \hline \end{tabular}
\end{table}
Table 2: Results of real time performance.  
**Author Contributions:** Conceptualization, M.H., W.G. and J.L.; methodology, M.H. and W.G.; software, M.H., Z.F., Z.C. and B.C.; validation, Z.C., J.L. and B.C.; formal analysis, M.H.; investigation, Z.C.; resources, W.G.; data curation, Z.F.; writing--original draft preparation, M.H. and Z.C.; writing--review and editing, M.H. and W.G.; visualization, J.L.; supervision, W.G. and Z.F.; project administration, W.G. and M.H.; funding acquisition, W.G. and M.H.  
**Funding:** This work was supported by the National Undergraduate Innovative and Entrepreneurial Training Program (No. 201810561217), and the Special Fund for the Cultivation of Guangdong College Students' Scientific and Technological Innovation (\"Climbing Program\" Special Fund) (No. pdih2017b0040, No. pdiha0028).  
**Conflicts of Interest:** The authors declare no conflict of interest.