Interference Cancellation and Proper Thresholding Using Deep Learning Method in Optical Camera Communication

During data collection from the images using rolling shutter effect in the optical camera communication, interference from the surrounding light source reduce the system performances. On the other hand, thresholding problem creates after getting the normalized intensity from the image when number of sources appear in the camera’s field of view. Therefore, we applied deep learning approach for removing the interfering light sources and use synchronous thresholding method for data correction. We also observed the performance of signal-error-rate of the system in different condition in Python environment.