We present a novel method for communicating between a camera and display by embedding and recovering hidden and dynamic information within a displayed image. A handheld camera pointed at the display can receive not only the display image, but also the underlying message. These active scenes are fundamentally different from traditional passive scenes like QR codes because image formation is based on display emittance, not surface reflectance. Detecting and decoding the message requires careful photometric modeling for computational message recovery. Unlike standard watermarking and steganography methods that lie outside the domain of computer vision, our message recovery algorithm uses illumination to optically communicate hidden messages in real world scenes. The key innovation of our approach is an algorithm that performs simultaneous radiometric calibration and message recovery in one convex optimization problem. By modeling the photometry of the system using a camera-display transfer function (CDTF), we derive a physics-based kernel function for support vector machine classification. We demonstrate that our method of optimal online radiometric calibration (OORC) leads to an efficient and robust algorithm for computational messaging between nine commercial cameras and displays.
From a computer vision point of view, the imaging process can be divided into two main components: photometry and geometry. The geometric aspects of image formation have been addressed to some extent in the watermarking community, and many techniques have been developed for robustness to geometric changes during the imaging process such as scaling, rotations, translations and general homography transformations @cite_9 @cite_33 @cite_30 @cite_13 @cite_14 @cite_27 @cite_15 . However, the photometry of imaging has largely been ignored. The rare mention of photometric effects @cite_16 @cite_39 in the watermarking literature doesn't define photometry with respect to illumination; instead photometric effects are defined as lossy compression, denoising, noise addition and lowpass filtering''. In fact, photometric attacks are sometimes defined as jpeg compression @cite_30 .
@cite_30 @cite_14 @cite_33 @cite_9 @cite_39 @cite_27 @cite_15 @cite_16 @cite_13
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Traditional watermarking schemes are sensitive to geometric distortions, in which synchronisation for recovering embedded information is a challenging task because of the disorder caused by rotation, scaling or translation (RST). The existing RST-resistant watermarking methods still have limitations with respect to robustness, capacity or fidelity. In this study, the authors address several major problems in RST-invariant watermarking. The first point is how to take advantage of the high RST resilience of scale-invariant feature transform (SIFT) features, which show good performance in terms of RST-resistant pattern recognition. Since many keypoint-based watermarking methods do not discuss cropping attacks, the second issue discussed in this study is how to resist cropping using a human visual system (HVS), which also helps us to eliminate computational complexity. The third issue is the investigation of an HVS-based watermarking strategy for extracting only feature points in the human attentive area. Lastly, a variable-length watermark synchronisation algorithm using dynamic programming is proposed. Experimental results show that the proposed algorithms are practical and show superior performance in comparison with many existing works in terms of watermark capacity, watermark transparency, and the resistance to RST attacks. Here we propose a new technique for the Watermarking to withstand the geometric attacks, which may occur during the transmission of the watermarked image. The underlying system was based on Direct Sequence Code Division Multiple Access (DS-CDMA). The algorithm for the normalization had been formulated for use in black and white images. The watermark was spreaded across the carrier image by using the pseudo-random noise sequences of optimal period and retrieval was made by the use of correlation. Private Key technique is used so the transmission is very secure. Matlab was used to implement the algorithm discussed here. In this paper, we present two watermarking approaches that are robust to geometric distortions. The first approach is based on image normalization, in which both watermark embedding and extraction are carried out with respect to an image normalized to meet a set of predefined moment criteria. We propose a new normalization procedure, which is invariant to affine transform attacks. The resulting watermarking scheme is suitable for public watermarking applications, where the original image is not available for watermark extraction. The second approach is based on a watermark resynchronization scheme aimed to alleviate the effects of random bending attacks. In this scheme, a deformable mesh is used to correct the distortion caused by the attack. The watermark is then extracted from the corrected image. In contrast to the first scheme, the latter is suitable for private watermarking applications, where the original image is necessary for watermark detection. In both schemes, we employ a direct-sequence code division multiple access approach to embed a multibit watermark in the discrete cosine transform domain of the image. Numerical experiments demonstrate that the proposed watermarking schemes are robust to a wide range of geometric attacks. A robust video watermarking scheme resilient to spatial desynchronization and photometric distortion is presented. The scheme is based on geometrically approximate invariant watermarking and adaptive watermarking, and it embeds watermark by modifying middle frequency component adaptively according to persistence of vision and Watson's DCT based visual model. Experimental results show that the proposed watermarking scheme is not only robust against spatial desynchronization and photometric distortion, but also robust against their combination. Furthermore, it can resist randomly frame inserting or frame dropping to some extent Watermarking, which belong to the information hiding field, has seen a lot of research interest. There is a lot of work begin conducted in different branches in this field. Steganography is used for secret communication, whereas watermarking is used for content protection, copyright management, content authentication and tamper detection. In this paper we present a detailed survey of existing and newly proposed steganographic and watermarking techniques. We classify the techniques based on different domains in which data is embedded. We limit the survey to images only. This paper proposes a novel content-based image watermarking method based on invariant regions of an image. The invariant regions are self-adaptive image patches that deform with geometric transformations. Three different invariant-region detection methods based on the scale-space representation of an image were considered for watermarking. At each invariant region, the watermark is embedded after geometric normalization according to the shape of the region. By binding watermarking with invariant regions, resilience against geometric transformations can be readily obtained. Experimental results show that the proposed method is robust against various image processing steps, including geometric transformations, cropping, filtering, and JPEG compression. This paper proposes a novel geometric distortion resilient image copy detection scheme based on Scale Invariant Feature Transform (SIFT) detector. By using the SIFT detector, the proposed copy detection scheme first construct a series of robust, homogenous, and larger size circular patches. And then, the cirque track division strategy and ordinal measure concept are introduced to generate a cirque-based ordinal measure feature vector for each circular patch. Besides, the ROC graph and MAP probability are utilized to estimate the two parameters (vector dimension and detection threshold) respectively. Experimental results and the related analysis show that the proposed scheme is robust to most of geometric and photometric distortions. Based on scale space theory and an image normalization technique, a new feature-based image watermarking scheme robust to general geometric attacks is proposed in this paper. First, the Harris-Laplace detector is utilized to extract steady feature points from the host image; then, the local feature regions (LFR) are ascertained adaptively according to the characteristic scale theory, and they are normalized by an image normalization technique; finally, according to the predistortion compensation theory, several copies of the digital watermark are embedded into the nonoverlapped normalized LFR by comparing the DFT mid-frequency magnitudes. Experimental results show that the proposed scheme is not only invisible and robust against common signals processing methods such as median filtering, sharpening, noise adding, and JPEG compression etc., but also robust against the general geometric attacks such as rotation, translation, scaling, row or column removal, shearing, local geometric distortion and combination attacks etc.