VisCode: Embedding Information in Visualization Images using Encoder-Decoder Network

We present an approach called VisCode for embedding information into visualization images. This technology can implicitly embed data information specified by the user into a visualization while ensuring that the encoded visualization image is not distorted. The VisCode framework is based on a deep n...

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Bibliographic Details
Published in:IEEE transactions on visualization and computer graphics Vol. 27; no. 2; pp. 326 - 336
Main Authors: Zhang, Peiying, Li, Chenhui, Wang, Changbo
Format: Journal Article
Language:English
Published: United States IEEE 01.02.2021
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:
Algorithms
Artificial neural networks
autocoding
Coders
Data visualization
Decoding
Embedding
Encoders-Decoders
Encoding
Image coding
Image color analysis
information steganography
Information visualization
Media
Performance evaluation
saliency detection
Scientific visualization
Visualization
visualization retargeting
ISSN:1077-2626, 1941-0506, 1941-0506
Online Access:Get full text
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Description
Summary:We present an approach called VisCode for embedding information into visualization images. This technology can implicitly embed data information specified by the user into a visualization while ensuring that the encoded visualization image is not distorted. The VisCode framework is based on a deep neural network. We propose to use visualization images and QR codes data as training data and design a robust deep encoder-decoder network. The designed model considers the salient features of visualization images to reduce the explicit visual loss caused by encoding. To further support large-scale encoding and decoding, we consider the characteristics of information visualization and propose a saliency-based QR code layout algorithm. We present a variety of practical applications of VisCode in the context of information visualization and conduct a comprehensive evaluation of the perceptual quality of encoding, decoding success rate, anti-attack capability, time performance, etc. The evaluation results demonstrate the effectiveness of VisCode.
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ISSN:1077-2626
1941-0506
1941-0506
DOI:10.1109/TVCG.2020.3030343