# Spectral Domain-Based Data-Embedding Mechanisms for Display-to-Camera Communication
###### Abstract
Therefore, instead of direct manipulation of image pixels, it is preferred to insert data into the coefficients that are robust under all available frequency coefficients. In this manner, the data are spread over many frequency coefficients. The data energy associated with a single coefficient becomes small and thus is not readily detectable in the spatial domain. This renders the data less susceptible to the noise while being transmitted over a wireless optical channel. This situation is analogous to that of spread-spectrum communications, which states that the signal energy at any single frequency is completely undetectable when any narrowband signal is transmitted over a massive bandwidth. Thus, frequency-based embedding is an attractive method to robustly embed data into an image for a D2C link. To embed data, the various types of frequency transformation such as Fourier, wavelet, and cosine transform are considered. Since the maintenance of visual quality of the data embedded image is crucial, the frequency coefficients must be selected such that the visual content of the original image remains unaffected despite data embedding. This topic was previously studied in the context of watermarking and steganography [14; 15; 16]. In [14], a robust hybrid watermarking algorithm was presented. Here, a discrete Wavelet transform (DWT) was combined with singular value decomposition (SVD); data were embedded into the DC coefficients of the high-low (HL) and low-high (LH) sub-bands. Similarly, in [15], a fast-discrete Cosine transform (FDCT) algorithm was used to enhance the computational performance of watermarking. Likewise, [PERSON] et al. [16] presented a secure algorithm for image watermarking that can be generalized to multimedia data, such as audio files and video clips. The embedding principle of digital watermarking is identical to that of D2C frequency-based data embedding. However, conventional watermarking does not consider the effect of the wireless optical channel, which greatly affects the reliability of communication performance. Previous studies [17; 18; 19] explored various methods by which data could be embedded into the frequency domain of an image; a display and a camera served as the transmitter and receiver respectively. In [17], discrete Fourier transform (DFT) coefficients were used to embed data by exploiting wireless orthogonal frequency division multiplexing (OFDM) modulation. The effects of perspective distortion of the transmitted image on the performance of the D2C system were evaluated under various vision transformation parameters. Similarly, [PERSON] et al. [18; 19] explored data embedding into specific frequency regions of an image using a parallel transmission VLC system. Popular transformation methods, including DWT and discrete cosine transform (DCT) [20], were evaluated. However, these studies have not explored how different types of encoding methods can be achieved in the spectral domain images by utilizing specific embedding factors. The details regarding the selection of frequency coefficients, the effects of the transmission distance \(D\), angle of capture \(AOC\), and wireless optical channel on D2C performance were not investigated either. Specifically, the generalization of these approaches with respect to the changes in the testing environment were not examined. In this paper, we explore various DCT-based data-embedding schemes in a D2C system. Unlike conventional spectral data-embedding schemes that do not consider the effects of the wireless transmission channel, we derive several data-embedding mechanisms using the DCT coefficients of an image. We consider the nature of the optical wireless channel and embed data into the robust spectral coefficients of the image, which is displayed on an electronic screen and captured by a camera at the receiver side. The decoder at the receiving end performs a geometric correction of the captured image, which is followed by a DCT to extract the embedded data from the frequency coefficients of the captured image.