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Author

Ioannis Pitas

Other affiliations: University of Bristol, University of York, University of Toronto  ...read more
Bio: Ioannis Pitas is an academic researcher from Aristotle University of Thessaloniki. The author has contributed to research in topics: Facial recognition system & Digital watermarking. The author has an hindex of 76, co-authored 795 publications receiving 24787 citations. Previous affiliations of Ioannis Pitas include University of Bristol & University of York.


Papers
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Journal ArticleDOI
TL;DR: An error-concealment scheme that is based on block-matching principles and spatio-temporal video redundancy is presented and proves to be satisfactory for packet error rates (PER) ranging from 1% to 10% and for video sequences with different content and motion and surpasses that of other EC methods under study.
Abstract: The MPEG-2 compression algorithm is very sensitive to channel disturbances due to the use of variable-length coding. A single bit error during transmission leads to noticeable degradation of the decoded sequence quality, in that part or an entire slice information is lost until the next resynchronization point is reached. Error concealment (EC) methods, implemented at the decoder side, present one way of dealing with this problem. An error-concealment scheme that is based on block-matching principles and spatio-temporal video redundancy is presented in this paper. Spatial information (for the first frame of the sequence or the next scene) or temporal information (for the other frames) is used to reconstruct the corrupted regions. The concealment strategy is embedded in the MPEG-2 decoder model in such a way that error concealment is applied after entire frame decoding. Its performance proves to be satisfactory for packet error rates (PER) ranging from 1% to 10% and for video sequences with different content and motion and surpasses that of other EC methods under study.

161 citations

Journal ArticleDOI
01 Nov 1999
TL;DR: Two modifications of the FKM and FVQ algorithms, based on a fuzzy vector distance definition, are proposed to handle the fuzzy data and utilize the quality measure, and the use of the quality via the proposed modified algorithms increases the performance of the fusion system.
Abstract: The use of clustering algorithms for decision-level data fusion is proposed. Person authentication results coming from several modalities (e.g., still image, speech), are combined by using fuzzy k-means (FKM) and fuzzy vector quantization (FVQ) algorithms, and a median radial basis function (MRBF) network. The quality measure of the modalities data is used for fuzzification. Two modifications of the FKM and FVQ algorithms, based on a fuzzy vector distance definition, are proposed to handle the fuzzy data and utilize the quality measure. Simulations show that fuzzy clustering algorithms have better performance compared to the classical clustering algorithms and other known fusion algorithms. MRBF has better performance especially when two modalities are combined. Moreover, the use of the quality via the proposed modified algorithms increases the performance of the fusion system.

160 citations

Journal ArticleDOI
TL;DR: The watermark robustness with respect to some very important image processing attacks, such as the translation, rotation, cropping, JPEG compression, and filtering, is demonstrated and tested by using Stirmark 3.1.
Abstract: A two-dimensional (2-D) signal with a variable spatial frequency is proposed as a watermark in the spatial domain. This watermark is characterized by a linear frequency change. It can be efficiently detected by using 2-D space/spatial-frequency distributions. The projections of the 2-D Wigner distribution-the 2-D Radon-Wigner distribution, are used in order to emphasize the watermark detection process. The watermark robustness with respect to some very important image processing attacks, such as for example, the translation, rotation, cropping, JPEG compression, and filtering, is demonstrated and tested by using Stirmark 3.1.

156 citations

Journal ArticleDOI
TL;DR: An application of the fractional Fourier transform for the multimedia copyright protection is proposed and the watermark robustness as well as statistical performance are considered.

155 citations

Journal ArticleDOI
TL;DR: A combined approach for facial feature extraction and determination of gaze direction is proposed that employs some improved variations of the adaptive Hough transform for curve detection, minima analysis of feature candidates, template matching for inner facial feature localization and active contour models for inner face contour detection.

151 citations


Cited by
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Journal ArticleDOI

[...]

08 Dec 2001-BMJ
TL;DR: There is, I think, something ethereal about i —the square root of minus one, which seems an odd beast at that time—an intruder hovering on the edge of reality.
Abstract: There is, I think, something ethereal about i —the square root of minus one. I remember first hearing about it at school. It seemed an odd beast at that time—an intruder hovering on the edge of reality. Usually familiarity dulls this sense of the bizarre, but in the case of i it was the reverse: over the years the sense of its surreal nature intensified. It seemed that it was impossible to write mathematics that described the real world in …

33,785 citations

Journal ArticleDOI
TL;DR: In this paper, the authors provide an up-to-date critical survey of still-and video-based face recognition research, and provide some insights into the studies of machine recognition of faces.
Abstract: As one of the most successful applications of image analysis and understanding, face recognition has recently received significant attention, especially during the past several years. At least two reasons account for this trend: the first is the wide range of commercial and law enforcement applications, and the second is the availability of feasible technologies after 30 years of research. Even though current machine recognition systems have reached a certain level of maturity, their success is limited by the conditions imposed by many real applications. For example, recognition of face images acquired in an outdoor environment with changes in illumination and/or pose remains a largely unsolved problem. In other words, current systems are still far away from the capability of the human perception system.This paper provides an up-to-date critical survey of still- and video-based face recognition research. There are two underlying motivations for us to write this survey paper: the first is to provide an up-to-date review of the existing literature, and the second is to offer some insights into the studies of machine recognition of faces. To provide a comprehensive survey, we not only categorize existing recognition techniques but also present detailed descriptions of representative methods within each category. In addition, relevant topics such as psychophysical studies, system evaluation, and issues of illumination and pose variation are covered.

6,384 citations

Journal ArticleDOI
TL;DR: In this article, the authors categorize and evaluate face detection algorithms and discuss relevant issues such as data collection, evaluation metrics and benchmarking, and conclude with several promising directions for future research.
Abstract: Images containing faces are essential to intelligent vision-based human-computer interaction, and research efforts in face processing include face recognition, face tracking, pose estimation and expression recognition. However, many reported methods assume that the faces in an image or an image sequence have been identified and localized. To build fully automated systems that analyze the information contained in face images, robust and efficient face detection algorithms are required. Given a single image, the goal of face detection is to identify all image regions which contain a face, regardless of its 3D position, orientation and lighting conditions. Such a problem is challenging because faces are non-rigid and have a high degree of variability in size, shape, color and texture. Numerous techniques have been developed to detect faces in a single image, and the purpose of this paper is to categorize and evaluate these algorithms. We also discuss relevant issues such as data collection, evaluation metrics and benchmarking. After analyzing these algorithms and identifying their limitations, we conclude with several promising directions for future research.

3,894 citations