ABSTRACT
This paper presents a technique for removing unnecessary QR code patterns from captured images of subjects using a U-Net type autoencoder. This study is a part of our series focusing on optical watermarking embedded invisibly in the light illuminating the subject. The purpose of optical watermarking is to include useful or valuable information about the subject in the captured images taken with a camera and provide it to the user as needed. We utilized QR codes as the watermarking in this study. A negative and a positive pattern are projected onto the subject alternately, making them invisible to the human eye. Although it is invisible to the human eye on the subject, the image taken by the camera contains positive or negative patterns, allowing users to extract information about the subject from the QR code in the captured image. However, if users want to save an image taken of a subject, the QR code is not necessary, and it is desirable to delete it after acquiring the necessary information, as it degrades the quality of the subject image. In this research, an image with a superimposed QR code on a subject image was created through simulation by multiplying the subject image and the QR code image. The autoencoder was then trained using the original subject image as the truth image. Using the trained model, we attempted to remove the QR code by inputting a subject image with a superimposed QR code that was not used during the training of the autoencoder. The evaluations of the difference from the truth image, measured using PSNR (Peak Signal to Noise Ratio) and SSIM (Structural Similarity), were 34 and 93, respectively, indicating that the QR code can be visually removed from the subject image.
- C.I. Podilchuk and E.J. Delp. 2001. “Digital watermarking: algorithms and applications”, IEEE Signal Processing Magazine, 18, 4, 33-46Google ScholarCross Ref
- Y. Zhang. 2009. "Digital Watermarking Technology: A Review," 2009 ETP International Conference on Future Computer and Communication, 250-252Google Scholar
- M. Chandra, S. Pandey and R. Chaudhary. 2010. "Digital watermarking technique for protecting digital images," 3rd International Conference on Computer Science and Information Technology, 226-233Google Scholar
- K. Uehira and M. Suzuki. 2008 "Digital Watermarking Technique Using Brightness-Modulated Light," in Proc. IEEE International Conference on Multimedia and Expo, 257–260Google Scholar
- Y. Ishikawa, K. Uehira, and Y. Yanaka. 2010. "Practical Evaluation of Illumination Watermarking Technique Using Orthogonal Transform", IEEE/OSA Journal of Display Technology, 6, 9, 351–358Google ScholarCross Ref
- H. Unno and K, Uehira. 2020. “Lighting technique for attaching invisible information onto real objects using temporally and spatially color-intensity modulated light”, IEEE Transactions on Industry Applications, 56, 6, 7202-7207Google ScholarCross Ref
- K. Uehira and H. Unno. 2020. “Technique for removing superimposed patterns on objects using GAN”, Proceedings of IEEE ICCE2020Google Scholar
- L Zhou, S. Fukushima, T. Naemura. 2014. “Dynamically reconfigurable framework for pixel-level visible light communication projector”, Proc. SPIE 8979, Emerging Digital Micromirror Device Based Systems and Applications VI, 89790JGoogle Scholar
- I. Kamei, T. Hiraki, S. Fukushima, T. Naemura. 2019. "PILC Projector: Image Projection with Pixel-Level Infrared Light Communication", IEEE Access, 7, 160768-160778Google ScholarCross Ref
- D. Cotting; M. Naef; M. Gross; H. Fuchs. 2004. “Embedding imperceptible patterns into projected images for simultaneous acquisition and display”, Third IEEE and ACM International Symposium on Mixed and Augmented RealityGoogle ScholarDigital Library
- Jingwen Dai; Chi-Kit Ronald Chung. 2013. “Embedding Invisible Codes Into Normal Video Projection: Principle, Evaluation, and Applications”, IEEE Transactions on Circuits and Systems for Video Technology, 23, 12, 2054-2066Google ScholarDigital Library
- Sharma A., Raut S. , Shimasaki K., Senoo T., Ishii I. 2021. “Visual-Feedback-Based Frame-by-Frame Synchronization for 3000 fps Projector-Camera Visual Light Communication”, Electronics (Web), 10, 14, 1631Google ScholarCross Ref
Recommendations
An Improved Algorithm for QR Code Image Binarization
ICVRV '14: Proceedings of the 2014 International Conference on Virtual Reality and VisualizationQR codes are the most widely used in two-dimensional barcodes nowadays. Image pre-processing is an important process to achieve QR code image recognition in complex conditions and binarization that directly determines the success or failure of the ...
Effective Color image watermarking scheme using YCbCr color space and QR code
A digital image watermarking technique is proposed to hide the relevant information in color digital images. The image is converted from RGB color space to YCbCr color space. This enables the algorithm to exploit characteristics of the Human Visual ...
QR code based image steganography via variable step size firefly algorithm and lifting wavelet transform
ICMLSC '18: Proceedings of the 2nd International Conference on Machine Learning and Soft ComputingThe Image steganography is the art of hiding secret message onto the source image. A good approach to the steganography must provide for the high stego image quality. An efficient Steganographic method is proposed for embedding secrete message into the ...
Comments