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Author

Iwan Setyawan

Other affiliations: Delft University of Technology
Bio: Iwan Setyawan is an academic researcher from Satya Wacana Christian University. The author has contributed to research in topics: Digital watermarking & Watermark. The author has an hindex of 10, co-authored 54 publications receiving 1114 citations. Previous affiliations of Iwan Setyawan include Delft University of Technology.


Papers
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Journal ArticleDOI
TL;DR: The authors begin by discussing the need for watermarking and the requirements and go on to discuss digitalWatermarking techniques based on correlation and techniques that are notbased on correlation.
Abstract: The authors begin by discussing the need for watermarking and the requirements. They go on to discuss digital watermarking techniques based on correlation and techniques that are not based on correlation.

789 citations

Proceedings ArticleDOI
TL;DR: In this paper, it was shown that the maximal number of detections that can be performed in a geometrical search is bounded by the maximum false positive detection probability required by the watermark application.
Abstract: One way of recovering watermarks in geometrically distorted images is by performing a geometrical search. In addition to the computational cost required for this method, this paper considers the more important problem of false positives. The maximal number of detections that can be performed in a geometrical search is bounded by the maximum false positive detection probability required by the watermark application. We show that image and key dependency in the watermark detector leads to different false positive detection probabilities for geometrical searches for different images and keys. Furthermore, the image and key dependency of the tested watermark detector increases the random-image-random-key false positive detection probability, compared to the Bernoulli experiment that was used as a model.

62 citations

Proceedings ArticleDOI
TL;DR: This paper presents an extension to the Differential Energy Watermarking algorithm, to use it in low bit-rate environment and evaluates its performance in terms of watermark capacity, robustness and visual impact.
Abstract: Digital video data distribution through the internet is becoming more common. Film trailers, video clips and even video footage from computer and video games are now seen as very powerful means to boost sales of the aforementioned products. These materials need to be protected to avoid copyright infringement issues. However, these materials are encoded at a low bit-rate to facilitate internet distribution and this poses a challenge to the watermarking operation. In this paper we present an extension to the Differential Energy Watermarking (DEW) algorithm, to use it in low bit-rate environment. We present the extension scheme and its evaluate its performance in terms of watermark capacity, robustness and visual impact.

33 citations

Journal ArticleDOI
TL;DR: This paper presents a face recognition method based on the combined kernel principal component analysis (KPCA) and support vector machine (SVM) methods, and shows that the combination of KPCA and SVM achieves a higher performance than other commonly-used methods.
Abstract: Face recognition is gaining enormous interest nowadays. However, the technical challenges to "teach" a computer to recognize faces have been very difficult. Many methods and approaches have been proposed in the literature. This paper presents a face recognition method based on the combined kernel principal component analysis (KPCA) and support vector machine (SVM) methods. First, the KPCA method is utilized to extract features from the input images. The SVM method is then applied to these extracted features to classify the input images. We compare the performance of this face recognition method to other commonly-used methods. Our experiments show that the combination of KPCA and SVM achieves a higher performance compared to the nearest neighbor classifier, support vector machine, and the combination of kernel principal component analysis and nearest neighbor classifier.

30 citations

Proceedings ArticleDOI
TL;DR: This paper proposes a method of objectively assessing the perceptual quality of geometrically distorted images based on the modeling of a complex, global geometric distortion using local, simpler geometric transformation models.
Abstract: One of the most active research area in the watermarking community is the research in dealing with geometric distortion. The geometric distortion problem has two aspects, namely its effect on watermark detectability and its effect on the perceptual quality of the watermarked data. Most research in this area has been concentrated on addressing the first aspect of the problem, and research on objective visual quality assessment of geometrically distorted images is not widely discussed in the literature. As a consequence, there is a lack of objective visual quality measurement for this class of distortion. In this paper we propose a method of objectively assessing the perceptual quality of geometrically distorted images. Our approach is based on the modeling of a complex, global geometric distortion using local, simpler geometric transformation models. The locality of this simpler geometric transformation determines the visual quality of the distorted images.

23 citations


Cited by
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01 Jan 1990
TL;DR: An overview of the self-organizing map algorithm, on which the papers in this issue are based, is presented in this article, where the authors present an overview of their work.
Abstract: An overview of the self-organizing map algorithm, on which the papers in this issue are based, is presented in this article.

2,933 citations

Book
24 Oct 2001
TL;DR: Digital Watermarking covers the crucial research findings in the field and explains the principles underlying digital watermarking technologies, describes the requirements that have given rise to them, and discusses the diverse ends to which these technologies are being applied.
Abstract: Digital watermarking is a key ingredient to copyright protection. It provides a solution to illegal copying of digital material and has many other useful applications such as broadcast monitoring and the recording of electronic transactions. Now, for the first time, there is a book that focuses exclusively on this exciting technology. Digital Watermarking covers the crucial research findings in the field: it explains the principles underlying digital watermarking technologies, describes the requirements that have given rise to them, and discusses the diverse ends to which these technologies are being applied. As a result, additional groundwork is laid for future developments in this field, helping the reader understand and anticipate new approaches and applications.

2,849 citations

Journal ArticleDOI
TL;DR: In this paper, a generalization of the well-known least significant bit (LSB) modification is proposed as the data-embedding method, which introduces additional operating points on the capacity-distortion curve.
Abstract: We present a novel lossless (reversible) data-embedding technique, which enables the exact recovery of the original host signal upon extraction of the embedded information. A generalization of the well-known least significant bit (LSB) modification is proposed as the data-embedding method, which introduces additional operating points on the capacity-distortion curve. Lossless recovery of the original is achieved by compressing portions of the signal that are susceptible to embedding distortion and transmitting these compressed descriptions as a part of the embedded payload. A prediction-based conditional entropy coder which utilizes unaltered portions of the host signal as side-information improves the compression efficiency and, thus, the lossless data-embedding capacity.

1,058 citations

Dissertation
01 Jan 2002

570 citations

01 Dec 1996

452 citations