This paper presents a correlation-based watermarking method for video using the similarity of adjacent frames. In general, the adjacent frames of a video sequence is very similar. In the proposed scheme, we use an adjoining frame in detection process instead of an original image in the watermarking scheme of Cox et al. So the proposed method does not need an original video sequence in detection process. When a watermarked video sequence is attacked by overwriting copy or frame dropping, the pair of the frames that is not adjoining in an original video sequence is used in detection process. However, since a watermark is embedded in a part of each frame and embedding positions are different for each frame in the proposed method, we can detect the watermark even from an overwriting-copied video sequence and a frame-dropped video sequence. Experimental results show that the proposed method is robust against overwriting copy and frame dropping. Moreover, it is shown from experimental results that the method has robustness to low bitrate MPEG compression and StirMark attack.

In this paper, the false-peaks problem of the conventional correlation-based video tracking is investigated using a simple mathematical analysis. To reduce the false detection problem, a selective-attention correlation measure is proposed. The problem with the conventional correlation measures is that all pixels in the reference block image are equally treated in the computation of the correlation measures irrespective of target or background pixels. Therefore, the more the reference block image includes background pixels, the higher probability of false-peaks is introduced due to the correlation between the background pixels of the reference block and those of the input search image. The proposed selective-attention correlation measure has different consideration according to target and background pixels in the matching process, which conform with the selective-attention property of human visual system. Various computer simulations validated these analyses and confirmed that the proposed selective-attention measure is effective to reduce considerably the probability of the false-peaks.

There are two main types of digital watermark systems. In the first, users are given their own detection programs by which to verify the presence of watermark in data they have in their possession. In the second, users must request such verification from a detection center. The disadvantage of the first type is the possibility that a user might be able to analyze the detection program sufficiently to be able to obtain the secret data (secret key) used to embed the watermark. The disadvantage of the second is the possibility that a center might give dishonest results. In this paper, we propose a watermark detection scheme that can be used to overcome the disadvantages of both: it prevents users from obtaining secret key, and it prevents a center from reporting dishonest results. Our scheme is based on a previously proposed scheme which nearly achieved the same goals but, unfortunately, allowed users to receive watermark detection results for data specially created by them so as to reveal, through the results, secret information about how a center created its watermarks. To overcome this drawback, we have developed new scheme by which a center can prove its detection results to a user without revealing any other information. This scheme was developed by extending the work found in. Moreover we provide an option that prevents the center from encroaching on a user's privacy. The resulting watermark detection scheme is the first that, in addition to protecting secret keys of watermarks from user-tampering, is also able to prevent a center from reporting dishonest results. Although the proposed scheme is introduced first using the patch-work watermarking system, it is straightforward to extend it to a scheme that uses the correlation-based watermarking system, which yields a more robust watermark detection scheme.

A novel data embedding method for high-quality images, e.g., an image with a peak signal-to-noise ratio of better than 60 [dB] is proposed in this paper. The proposed method precisely generates a watermarked image of the desired and high quality for any images. To do this, this method considers the finite word-length of a luminance value of pixels, i.e., both quantization errors and the range limitation of luminance. The proposed method embeds a watermark sequence, modulated by the mechanism of a spread spectrum scheme, into the dc values of an image in the spatial domain. By employing spread spectrum technology as well as embedding a watermark into the dc values, this method guarantees the high image quality and, simultaneously, provides adequate JPEG tolerance.

An efficient algorithm is proposed for the adaptive sizing of a tracking window in correlation-based video tracking. Since a tracking window specifies a support region when estimating a target displacement, the ability to adapt the window size relative to a moving target significantly influences the performance of video tracking. The basic strategy of the proposed algorithm is to maintain the occupancy rate of the target in the tracking window within a specified range. As such, the proposed algorithm measures the occupancy rate using the ratio of the power of the spatial gradients in the edge subwindows, which edge the tracking window, to that in the tracking window. In addition, the level of any complex background and additive white noise is also evaluated to reduce their effect on the gradients. Experimental results using various artificial and real sequences confirm that the proposed algorithm can effectively adjust a tracking window to a moving target and is robust to a complex background and noise.