An Image Processing Based Blur Reduction Technique in Smartphone-to-Smartphone Visible Light Communication System

TL;DR

This paper introduces an image processing technique to reduce blur in smartphone-to-smartphone visible light communication, enhancing data recovery efficiency across various conditions.

Contribution

It proposes a novel image processing method that reduces blur and improves data recovery in S2SVLC systems, tested with practical experiments under diverse conditions.

Findings

Achieved 96% data recovery efficiency in experiments.

Effective in different lighting, distance, and orientation conditions.

Improves recognition efficiency and data rate in S2SVLC.

Abstract

In this paper, we present a blur reduction technique for smartphone-to-smartphone visible light communications (S2SVLC). The key technique it to avoid the repeated scanning of the transmitted data and to lower the amount of data discarded at the receiver end of the S2SVLC system. This image processing method will improve the system recognition efficiency and data rate. The proposed method includes converting the red-green-blue (RGB) image into grayscale, applying contrast enhancement, scaling and binarizing the image to reduce the blur levels in the image. The experiment includes practical data acquisition and further processing and estimation in MATLAB. The experiment is carried out in different conditions like distance, rotation, and tilt also considering different surrounding illuminations like ambient light and no light conditions to estimate the blur levels in S2SVLC. In this experimental investigation two types of coding, American Standard code for information interchange (ASCII), and quick response (QR) code are used for data transmission in S2SVLC. The obtained results indicate that, the proposed technique is proven to improve the recovery efficiency to 96% in the receiver end at different conditions.