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Related Experiment Video

Updated: Jul 16, 2025

Simultaneously Capturing Real-time Images in Two Emission Channels Using a Dual Camera Emission Splitting System: Applications to Cell Adhesion
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Dense D2C-Net: dense connection network for display-to-camera communications.

Nilesh Maharjan, Lakpa Dorje Tamang, Byung Wook Kim

    Optics Express
    |September 15, 2023
    PubMed
    Summary
    This summary is machine-generated.

    This study presents Dense D2C-Net, a novel display-to-camera (D2C) method using deep convolutional neural networks (DCNNs) to embed data in images. The scheme achieves superior performance in real-world tests, maintaining visual quality and data integrity.

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    Area of Science:

    • Computer Science
    • Electrical Engineering
    • Information Technology

    Background:

    • Display-to-camera (D2C) communication enables data transfer via visual content.
    • Existing DCNN-based D2C schemes face challenges in visual quality and robustness.

    Purpose of the Study:

    • Introduce Dense D2C-Net, a novel DCNN-based scheme for unobtrusive data embedding and extraction via visual content.
    • Enhance data integrity and visual quality in D2C communication.

    Main Methods:

    • Developed Dense D2C-Net, a DCNN architecture with inter-layer connections and feature reuse for encoding.
    • Utilized the Y channel for embedding binary data due to its robustness.
    • Integrated hybrid layers and noise layers to improve data hiding and mitigate channel distortions.
    • Employed 2D convolutional layers for data extraction at the decoder.

    Main Results:

    • Demonstrated superior performance of Dense D2C-Net compared to conventional DCNN-based D2C schemes.
    • Validated effectiveness across various parameters: transmission distance, capture angle, display brightness, and camera resolution.
    • Maintained high visual quality of the cover image with embedded data.

    Conclusions:

    • Dense D2C-Net offers a robust and efficient solution for display-to-camera communication.
    • The proposed scheme provides a significant advancement in embedding and extracting data through visual content.
    • Effective for real-world applications utilizing smartphone cameras and digital displays.