# Spectral Domain-Based Data-Embedding Mechanisms for Display-to-Camera Communication
###### Abstract  
Recently, digital displays and cameras have been extensively used as new data transmission and reception devices in conjunction with optical camera communication (OCC) technology. This paper presents three types of frequency-based data-embedding mechanisms for a display-to-camera (D2C) communication system, in which a commercial digital display transmits information and an off-the-shelf smartphone camera receives it. For the spectral embedding, sub-band coefficients obtained from a discrete cosine transform (DCT) image and predetermined embedding factors of three embedding mechanisms are used. This allows the data to be recovered from several types of noises induced in wireless optical channels, such as analog-to-digital (A/D) and digital-to-analog (D/A) conversion, rotation, scaling, and translation (RST) effects, while also maintaining the image quality to normal human eyes. We performed extensive simulations and real-world D2C experiments using several performance metrics. Through the analysis of the experimental results, it was shown that the proposed method can be considered as a suitable candidate for the D2C system in terms of the achievable data rate (ADR), peak signal-to-noise ratio (PSNR), and the bit error rate (BER). visible light communication; display-to-camera communication; data embedding; discrete cosine transform +
Footnote †: journal: 2021  
Previous D2C approaches [7; 8; 9; 10] mainly considered data embedding in the image spatial domain. In [7], the alpha channel was used to embed data into the translucency change of image pixels; the pixel RGB values were kept unchanged. The INFRAME [8] system enabled \"dual-mode full-frame communication\" between devices and the human eye. Here, data multiplexing into the full frame of a display unit was achieved by exploiting the concept of complementary frames, where two frames were mutually complementary in terms of the pixel luminance level. Similarly, in the DisCo system [9], data were transmitted by temporally modulating the brightness of the digital display at a very high frequency. Using a rolling shutter camera, transmitted messages were acquired by converting the temporally modulated incident light into a spatial flicker pattern. The SoftLight system [10] used a channel-coding approach that automatically adapts the data transmission rate to different scenarios; suggestions on how to exploit expanded color modulation and coding of bit-level rate-less transmissions of low computational complexity were provided. Quick response (QR) codes [11] and two-dimensional (2D) color barcodes [12; 13] are also considered as a D2C technology where barcoding can be used to embed data. In the COBRA system [12], data were encoded using specially designed 2D color barcodes and streamed between a small screen and the low-speed camera of a smartphone. The size and layout of the code blocks were designed to deal with image blurring during capture in mobile environments; the system allowed for real-time decoding and image processing. Similarly, in the Rainbow system [13], a high-capacity barcode layout allows for flexible frame synchronization and accurate code extraction. Here, to enhance the robustness of the system, \"progressive code locator detection\" and color recognition were incorporated. Generally, spatial embedding is vulnerable to various circumstances occurring in a wireless optical channel. The spatial component of an image is described by the pixel intensity, which can be severely affected by ambient lighting and noise present in the wireless optical channel. This noise alters the color intensity of image pixels. The variation in pixel intensity severely compromises the embedded data, which therefore must be explicitly placed in perceptually significant components of the image. When an image is transformed into the spectral domain, its frequency coefficients provide vital information about the image. These coefficients determine the rate of change in pixel values in the spatial domain (i.e., the edges and smooth regions of the image).