Methods that embed data into printed images and retrieve data from printed images captured using the camera of a mobile device have been proposed. Evaluating these methods requires printing and capturing actual embedded images, which is burdensome. In this paper, we propose a method for reducing the workload for evaluating the performance of data embedding algorithms by simulating the degradation caused by printing and capturing images using generative adversarial networks. The proposed method can represent various captured conditions. Experimental results demonstrate that the proposed method achieves the same accuracy as detecting embedded data under actual conditions.
Masahiro YASUDA
Kansai University
Soh YOSHIDA
Kansai University
Mitsuji MUNEYASU
Kansai University
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Masahiro YASUDA, Soh YOSHIDA, Mitsuji MUNEYASU, "New Performance Evaluation Method for Data Embedding Techniques for Printed Images Using Mobile Devices Based on a GAN" in IEICE TRANSACTIONS on Fundamentals,
vol. E106-A, no. 3, pp. 481-485, March 2023, doi: 10.1587/transfun.2022SML0003.
Abstract: Methods that embed data into printed images and retrieve data from printed images captured using the camera of a mobile device have been proposed. Evaluating these methods requires printing and capturing actual embedded images, which is burdensome. In this paper, we propose a method for reducing the workload for evaluating the performance of data embedding algorithms by simulating the degradation caused by printing and capturing images using generative adversarial networks. The proposed method can represent various captured conditions. Experimental results demonstrate that the proposed method achieves the same accuracy as detecting embedded data under actual conditions.
URL: https://global.ieice.org/en_transactions/fundamentals/10.1587/transfun.2022SML0003/_p
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@ARTICLE{e106-a_3_481,
author={Masahiro YASUDA, Soh YOSHIDA, Mitsuji MUNEYASU, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={New Performance Evaluation Method for Data Embedding Techniques for Printed Images Using Mobile Devices Based on a GAN},
year={2023},
volume={E106-A},
number={3},
pages={481-485},
abstract={Methods that embed data into printed images and retrieve data from printed images captured using the camera of a mobile device have been proposed. Evaluating these methods requires printing and capturing actual embedded images, which is burdensome. In this paper, we propose a method for reducing the workload for evaluating the performance of data embedding algorithms by simulating the degradation caused by printing and capturing images using generative adversarial networks. The proposed method can represent various captured conditions. Experimental results demonstrate that the proposed method achieves the same accuracy as detecting embedded data under actual conditions.},
keywords={},
doi={10.1587/transfun.2022SML0003},
ISSN={1745-1337},
month={March},}
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TY - JOUR
TI - New Performance Evaluation Method for Data Embedding Techniques for Printed Images Using Mobile Devices Based on a GAN
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 481
EP - 485
AU - Masahiro YASUDA
AU - Soh YOSHIDA
AU - Mitsuji MUNEYASU
PY - 2023
DO - 10.1587/transfun.2022SML0003
JO - IEICE TRANSACTIONS on Fundamentals
SN - 1745-1337
VL - E106-A
IS - 3
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - March 2023
AB - Methods that embed data into printed images and retrieve data from printed images captured using the camera of a mobile device have been proposed. Evaluating these methods requires printing and capturing actual embedded images, which is burdensome. In this paper, we propose a method for reducing the workload for evaluating the performance of data embedding algorithms by simulating the degradation caused by printing and capturing images using generative adversarial networks. The proposed method can represent various captured conditions. Experimental results demonstrate that the proposed method achieves the same accuracy as detecting embedded data under actual conditions.
ER -