Digital watermarking for camera-captured images based on just noticeable distortion and Wiener filtering☆
Introduction
Digital media can be easily reproduced, especially digital images, and it is very difficult to distinguish illegal copies from the legal ones. This can lead to issues in many developing countries since it directly affects media owners/creators, and discourages them from inventing/developing future works. To address this problem, digital watermarking can be used to provide a mechanism for reliably verifying ownership of the distributed digital media. Digital image watermarking is used to embed secret digital information known as a “watermark” imperceptibly into a host digital image before distributing it to the public [1]. The quality degradation of a watermarked image must be unnoticeable by an observer of the image, while it is difficult for unauthorized person to modify, destroy or remove the embedded watermark. When the watermarked image is copied, the watermark will also be copied to the new image, and can later be extractable so the watermark can be “read” in order to provide electronic proof of ownership of such image [2]. This approach is commonly known as robust image watermarking, which is different from fragile image watermarking or image forensics approaches used for image authentication purposes [1].
The rapid growth of technology has led to the development of electronic devices. Particularly, printers and digital cameras are common devices used to publish and to reproduce documents. Digital images can be easily printed and rapidly distributed. For example, a digital image copied from Facebook and then printed on a poster or a printout contains such an image for an advertisement without permission from the owner (see Fig. 1). The copied and printed image is used and misunderstood by people that it belongs to someone else, not the real owner. Hence, his copyright, i.e. a legal right that grants the real owner of that image for its use, is violated. In this circumstance, if the original digital image contains a watermark, a digital version can be reproduced using a digital camera. In this paper we shall refer to this image as a “camera-captured image”, and investigate how an original image can be watermarked such that the embedded watermark will survive in a camera-captured version of the image. Note that the camera-captured image will be severely distorted from the printing and camera-capturing processes, resulting in an inaccuracy of the extracted watermark.
Various image watermarking methods have been proposed and shown to be robust against various types of distortions, e.g. rotation, scaling and translation (RST), shearing, etc. [3], [4], [5], [6], [7]. A few pioneer works on watermarking for camera-captured image has also been proposed. For example, a fast watermark detection method from a printed image proposed by Nakamura et al. [8] in 2004, where a camera phone was used to obtain a camera-captured image. With the help of a frame added around the image, the method was proved to be sufficiently robust against small geometric distortions. The captured image however needed to be aligned in front of the target image. Later, Takeuchi et al. [9] proposed a compensation method for lens and perspective-projective distortions in order to improve the correctness of watermark extracted from the captured image. Although the method was robust against both distortions, the effects of RST distortions were not considered and demonstrated. Kim et al. [10] proposed to embed a watermark repeatedly in form of a pseudorandom vector, while the amounts of the RST and perspective-projective distortions were reduced by using a tripod in the camera-capturing process, and by manually resizing and cropping the camera-captured image to its original size. Lee et al. [11] proposed a watermarking method based on local autocorrelation function (LACF) that was robust to Digital-to-Analog/Analog-to-Digital conversion (DAC/ADC), RST distortions, and perspective-projective distortion, which commonly occurred during the illegal copying of cinema footage. Conceptually, a watermark pattern was generated and added into part of the video frames in the spatial domain by taking an optimized Human Visual System (HVS). In detection process, the Weiner filter was used to predict the original video frame, while the LACF was used to estimate and recover geometric distortions for watermark synchronization purpose. Their method was experimentally proved to be robust against such distortions for video applications. In 2012, a periodic pattern-based watermarking method for interactive posters was proposed by Pramila et al. [12]. Basically, four watermark bits together with error control codes were used to generate particular 2-D patterns. The host image was divided into 9 successive blocks and used for patterns embedding separately. The technique based on enhanced peak detection with filtering was used to detect the angle of each embedded pattern, and the result was calculated and decoded to recover the four watermark bits. Although the method was proved to be robust against the RST and perspective-projective distortions, it suffered from a low embedding capacity, i.e. four watermark bits could only be embedded into each block of a host image.
In this paper, we present a new digital watermarking method for camera-captured images. Our method is designed to achieve both imperceptible watermark embedding and reliable watermark extraction from a printed image captured by a digital camera. In the watermark embedding process, a Gaussian based just noticeable distortion value, JNDG, is proposed for adjusting the watermark strength. In the watermark extraction process, three sub-processes are proposed, that is, an image registration technique based on a projective transformation is used for reducing geometric distortions, a color restoration technique based on the Color Mismatch Model with the RGB Speeded-Up Robust Features and local histogram equalization descriptors is used for decreasing pixel value distortions, and a prediction of original image component based on a modified 3 × 3 spatial domain Weiner filter is used for predicting original image component. Since various distortions are greatly introduced during the printing and camera-capturing processes, in the proposed watermarking method, the watermarked image is used to help decrease such distortions. In the next section, an overview of digital watermarking for camera-captured images is described. Details of our proposed watermark embedding and extraction processes are then presented in Section 3. Experimental settings are given in Section 4. The results are next shown and discussed in Section 5. The conclusion is in Section 6.
Section snippets
Overview of digital watermarking for camera-captured images
From Fig. 2, the entire system composes of four processes, namely, watermark embedding, printing, camera-capturing, and watermark extraction. In the embedding process, a watermark is embedded into a host color image with a help of secret key for hiding its position and value. Watermarked image is produced as an output, and passed through the printing and camera-capturing processes. The printing process reproduces the watermarked image using printers, e.g. inkjet, laser printers, etc., to obtain
Proposed watermarking method
The proposed watermarking method consists of two main processes: watermark embedding and watermark extraction.
Experimental settings and evaluation methods
Two sets of test images, i.e. photographic and computer-generated images, each with low, medium and high details, were used in the experiments. The detail level within each test image was classified in accordance with the criteria in [34], where an image’s content with a large amount of detail can be distinctly represented by a binary image format. Two 256 × 256 pixels color images were selected from [35], [36], [37] for each image type and detail level, so that twelve images in total were
Determination of a practical threshold
The validity of a watermark can be numerically evaluated by a NC based threshold. This threshold was determined by a statistical method called false alarm probability and used to differentiate the extracted watermark from a false one. The false alarm probability is the probability to detect a watermark in an image that is not watermarked or is watermarked with a different watermark than the one under investigation [44], and was determined by investigating the NC from 1000 different versions of
Conclusion
We have presented a new watermarking method for camera-captured images. In the proposed method, every pixel in the host image was used to carry a watermark bit, so that embedding a binary image with the same size as the host image was possible. Without distortions from the printing and camera-capturing processes, our proposed method was shown to succeed the watermark extraction reliably. With the distortions introduced, its reliable extraction was still achievable on a certain level, depending
Acknowledgments
This work was financially supported from the Thailand Research Fund through the Royal Golden Jubilee Ph.D. Program (Grant No. PHD/0111/2553) and King Mongkut’s University of Technology Thonburi.
Kharittha Thongkor was born in Uttaradit, Thailand, in 1985. She received B.Eng. and M.Eng. degrees in Electronics and Telecommunication Engineering and Computer Engineering from King Mongkut’s University of Technology Thonburi (KMUTT), Thailand, in 2007 and 2010, respectively. She is currently a lecturer at Department of Computer Engineering, Kasetsart University Sriracha Campus, and pursuing a PhD. Degree in Computer Engineering, KMUTT.
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Kharittha Thongkor was born in Uttaradit, Thailand, in 1985. She received B.Eng. and M.Eng. degrees in Electronics and Telecommunication Engineering and Computer Engineering from King Mongkut’s University of Technology Thonburi (KMUTT), Thailand, in 2007 and 2010, respectively. She is currently a lecturer at Department of Computer Engineering, Kasetsart University Sriracha Campus, and pursuing a PhD. Degree in Computer Engineering, KMUTT.
Thumrongrat Amornraksa received the M.Sc. and Ph.D. degrees from University of Surrey, England, in 1996 and 1999, respectively. He is currently an associate professor in the Department of Computer Engineering, King Mongkut’s University of Technology Thonburi (KMUTT). His research interests are digital watermarking and digital image processing.
Edward J. Delp received his BSEE and MS degrees from the University of Cincinnati, a PhD degree from Purdue University and an Honorary Doctor of Technology from the Tampere University of Technology, Finland. He is currently the Charles William Harrison distinguished professor of electrical and computer engineering and professor of biomedical engineering and professor of psychological sciences (courtesy). His research interests include multimedia security, multimedia systems, image and video compression, medical imaging, communication, information theory.
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This paper has been recommended for acceptance by Zicheng Liu.