Comparison of thresholding schemes for visible light communication using mobile-phone image sensor

Abstract

Based on the rolling shutter effect of the complementary metal-oxide-semiconductor (CMOS) image sensor, bright and dark fringes can be observed in each received frame. By demodulating the bright and dark fringes, the visible light communication (VLC) data logic can be retrieved. However, demodulating the bright and dark fringes is challenging as there is a high data fluctuation and large extinction ratio (ER) variation in each frame due. Hence proper thresholding scheme is needed. In this work, we propose and compare experimentally three thresholding schemes; including third-order polynomial curve fitting, iterative scheme and quick adaptive scheme. The evaluation of these three thresholding schemes is performed.

Thresholding schemes for visible light communications with CMOS camera using entropy-based algorithms

“…It is observe that the smoothing is an important part to improvement the performance. We also compare the BER and processing time of our proposed entropy thresholding schemes with other thresholding schemes reported in [14], such as quick adaptive, polynomial and iterative thresholding schemes as shown in Fig. 4(b) and 4(c).…”

“…Several thresholding schemes have been proposed, such as using the third order polynomial fitting [14]; however, it is not actuate enough for the fast changing data, particularly at high data rate (i.e. low pixel per bit case).…”

Optical Camera Communications: Principles, Modulations, Potential and Challenges

“…In RS, however, we have the following issues: (i) the blooming effect, which is the difference of light intensity between the area around the light source and the remaining frame area [23,74,77,78] and (ii) demodulation of the bright and dark fringes, which is challenging, due to its high data fluctuation and a large variation in the extinction ratio (ER), i.e., a significant blooming effect, see Figure 22. To mitigate the blooming effect, a suitable threshold scheme is required to level out the intensity across the captured frames so that an accurate binary threshold can be applied in order to demodulate the captured bit stream [74,79]. There are a number of image processing-based threshold schemes including 3rd order polynomial curve fitting, the iterative method [80], and quick adaptive method [81].…”

“…The quick adaptive thresholding utilizes a moving average calculation of grayscale values of pixels across the image rows [79,81]. The binary threshold is then set at the center row of the moving average results.…”

“…The iterative operation determines an initial grayscale value per each section and then divides the section into two subsets prior to averaging using addition and division by 2. Thus, it yields the ultimate grayscale values that are employed in the binary thresholding scheme [79].…”