GSyncCode: Geometry Synchronous Hidden Code for One-step Photography Decoding.
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| Title: | GSyncCode: Geometry Synchronous Hidden Code for One-step Photography Decoding. |
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| Authors: | Zhao, Chengxin, Ling, Hefei, Shen, Jialie, Fang, Han, Xie, Sijing, Fang, Yaokun, Li, Zongyi, Li, Ping |
| Source: | ACM Transactions on Multimedia Computing, Communications & Applications; Feb2025, Vol. 21 Issue 2, p1-21, 21p |
| Subject Terms: | TWO-dimensional bar codes, VISION, BAR codes, DATA extraction, HYPERLINKS |
| Abstract: | Invisible hyperlinks and hidden barcodes have recently emerged as a hot topic in offline-to-online messaging, where an invisible message or barcode is embedded in an image and can be decoded via camera shooting. Current schemes involve a two-step decoding process: starting with vertex localization of the embedded region to correct the perspective distortion introduced by shooting, followed by decoding the message from the corrected region. However, vertex localization can be complex and time-consuming, which affects the efficiency and accuracy of message decoding. To address this issue, this article proposes a geometry synchronous decoding scheme called GSyncCode, allowing for one-step extraction of a Data Matrix code from the photograph. Instead of correction before decoding, GSyncCode directly decodes a geometry-transformed Data Matrix that is synchronized with the embedded region. A barcode scanner is then used to efficiently retrieve messages. We design a Haar transform-based encoder HaarUNet and a HaarLoss visual function to select the key component of the Data Matrix for embedding. They improve the visual quality of the embedded image by reducing redundant embedding signals. Extensive simulated and real-world experiments demonstrate the superiority of GSyncCode in both decoding efficiency and accuracy. Our codes are published at: https://github.com/zcx-language/GSyncCode. [ABSTRACT FROM AUTHOR] |
| Copyright of ACM Transactions on Multimedia Computing, Communications & Applications is the property of Association for Computing Machinery and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Complementary Index |
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