Harnessing Spectral Domain: Comprehensive Insights into Display Field Communication

Display Field Communication (DFC) has emerged as a pivotal technique in the realm of hidden screen-camera communication, leveraging the advantages of the frequency-domain characteristics of an image frame. As DFC embeds data at a designated spectral band of a frequency-domain frame, the data remain hidden in the spatial domain during normal viewing and can only be decoded by a camera. This work provides a comprehensive overview of DFC, outlining its principle, recent advancements, and challenges. In particular, we discuss data embedding and detection techniques and compare the performance of some of DFC techniques. Additionally, challenges are discussed to improve the robustness of the DFC schemes including error correction strategies and machine learning algorithms. This paper indicate substantial potential for DFC in diverse applications, from Internet of Things connectivity to augmented reality interfaces.

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Publication Details

Published
2024-11-03
DOI
https://doi.org/10.1109/icce-asia63397.2024.10773699
Primary Topic
Experimental Learning in Engineering
Type
article
Field-Weighted Citation Impact
0.00

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article

Harnessing Spectral Domain: Comprehensive Insights into Display Field Communication

Sung‐Yoon Jung, Pankaj Singh, Ju-Hyun Kim
Experimental Learning in Engineering
article

Harnessing Spectral Domain: Comprehensive Insights into Display Field Communication

Sung‐Yoon Jung, Pankaj Singh, Ju-Hyun Kim
article en

Abstract

Display Field Communication (DFC) has emerged as a pivotal technique in the realm of hidden screen-camera communication, leveraging the advantages of the frequency-domain characteristics of an image frame. As DFC embeds data at a designated spectral band of a frequency-domain frame, the data remain hidden in the spatial domain during normal viewing and can only be decoded by a camera. This work provides a comprehensive overview of DFC, outlining its principle, recent advancements, and challenges. In particular, we discuss data embedding and detection techniques and compare the performance of some of DFC techniques. Additionally, challenges are discussed to improve the robustness of the DFC schemes including error correction strategies and machine learning algorithms. This paper indicate substantial potential for DFC in diverse applications, from Internet of Things connectivity to augmented reality interfaces.

Yeungnam University (KR)
National Research Foundation of Korea
Openalex Percentile: Top 63%
Experimental Learning in Engineering
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