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2007 Article Unknown

A closed-form nonparametric Bayesian estimator in the wavelet domain of images using an approximate alpha-stable prior - Comment
Achim A., Kuruoglu E. E., Bezerianos A., Tsakalides P.
The purpose of this commentary is to point out that the paper by Boubchir and Fadili (B-F) [Boubchir, L., Fadili, J.M., 2006. A closedform nonparametric Bayesian estimator in the wavelet domain of images using an approximate alpha-stable prior. Pattern Recognit. Lett. 27, 1370-1382] is little more than a paraphrase of earlier work in [Achim, A., Bezerianos, A., Tsakalides, P., 2001. Novel Bayesian multiscale method for speckle removal in medical ultrasound images. IEEE Trans. Med. Imag. 20 (August), 772-783; Kuruoglu, E.E., Molina, C., Fitzgerald, W.J., 1998. Approximation of a-stable probability densities using finite Gaussian mixtures. In: Proc. EUSIPCO'98 (September); Portilla, J., Strela, V., Wainwright, M.J., Simoncelli, E.P., 2003. Image denoising using scale mixtures of Gaussians in the wavelet domain. IEEE. Trans. Image. Proc. 12 (November), 1338-1351]. Essentially, B-F purport to propose an algorithm for image denoising based on scale mixtures of Gaussians in the wavelet domain, an approach well documented in [Portilla, J., Strela, V., Wainwright, M.J., Simoncelli, E.P., 2003. Image denoising using scale mixtures of Gaussians in the wavelet domain. IEEE. Trans. Image. Proc. 12 (November), 1338-1351]. In achieving this, B-F make use of a known method for approximating alpha-stable distributions previously proposed by Kuruoglu and co-workers [Kuruoglu, E.E., 1998. Signal processing in alpha-stable noise environments:Aleast lp-norm approach. Ph.D. thesis, University of Cambridge, Cambridge; Kuruoglu, E.E., Molina, C., Fitzgerald, W.J., 1998. Approximation of alpha-stable probability densities using finite Gaussian mixtures. In: Proc. USIPCO'98 (September)], but without referring to their work. Together, the above observations do not entitle B-F to claim to have developed a new algorithm. In addition, we show that B-F [2006; Fadili, J.M., Boubchir, L., 2005. Analytical form for a Bayesian wavelet estimator of images using the Bessel K form densities. IEEE Trans. Image Process. 14 (2), 231-240] include unfair comments and comparison vis-a`-vis of the method proposed in our early work [Achim, A., Bezerianos, A., Tsakalides, P., 2001. Novel Bayesian multiscale method for speckle removal in medical ultrasound images. IEEE Trans. Med. Imag. (August) 20, 772-783].Source: Pattern recognition letters 28 (2007): 1845–1847.

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2007 Article Unknown

Image separation using particle filters
Costagli M., Kuruoglu E. E.
In this work, we will analyze the problem of source separation in the case of superpositions of different source images, which need to be extracted from a set of noisy observations. This problem occurs, for example, in the field of astrophysics, where the contributions of various Galactic and extra-Galactic components need to be separated from a set of observed noisy mixtures. Most of the previous work on the problem performed blind source separation, assuming noiseless models, and in the few cases when noise is taken into account, it is assumed that it is Gaussian and space-invariant. In this paper we review the theoretical fundamentals of particle filtering, an advanced Bayesian estimation method which can deal with non-Gaussian non-linear models and additive space-varying noise, and we introduce a hierarchical model and a fusion of multiple particle filters for the solution of the image separation problem. Our simulations on realistic astrophysical data show that the particle filter approach provides significantly better results in comparison with one of the most widespread algorithms for source separation (FastICA), especially in the case of low SNR.Source: Digital signal processing (Print) 17 (2007): 935–946. doi:10.1016/j.dsp.2007.04.003
DOI: 10.1016/j.dsp.2007.04.003

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2007 Article Unknown

Long correlation Gaussian random fields: parameter estimation and noise reduction
Caiafa C., Proto A., Kuruoglu E. E.
In this paper, a parametric model for Gaussian random fields (GRFs) with long-correlation feature, namely the long correlation GRF (LC-GRF), is studied. Important properties of the model are derived and used for developing new parameter estimation algorithms and for constructing an optimum noise reduction filter. In particular, a novel iterative maximum likelihood estimation (MLE) algorithm is proposed for estimating the parameters of the model from a sample image, and the expectation-maximization (EM) algorithm is proposed for estimating the signal and noise variances given a noisy image. The optimal Wiener filter is derived making use of the parametric form of the model for the noise reduction under additive white Gaussian noise (WGN). Also the theoretic performance of the filter is obtained and its behavior is analyzed in terms of the long-correlation feature of the model. The effectiveness of the presented algorithms is demonstrated through experimental results on synthetic generated GRFs. An application to the restoration of cosmic microwave background (CMB) images in the presence of additive WGN is also presented.Source: Digital signal processing (Print) 17 (2007): 819–835. doi:10.1016/j.dsp.2007.01.001
DOI: 10.1016/j.dsp.2007.01.001

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2007 Article Unknown

Object tracking in a stereo and infrared vision system
Colantonio S., Benvenuti M., Di Bono M. G., Pieri G., Salvetti O.
In this paper, we deal with the problem of real-time detection, recognition and tracking of moving objects in open and unknown environments using an infrared (IR) and visible vision system. A thermo-camera and two stereo visible-cameras synchronized are used to acquire multi-source information: three-dimensional data about target geometry and its thermal information are combined to improve the robustness of the tracking procedure. Firstly, target detection is performed by extracting its characteristic features from the images and then by storing the computed parameters on a specific database; secondly, the tracking task is carried on using two different computational approaches. A Hierarchical Artificial Neural Network (HANN) is used during active tracking for the recognition of the actual target, while, when partial occlusions or masking occur, a database retrieval method is used to support the search of the correct target followed. A prototype has been tested on case studies regarding the identification and tracking of animals moving at night in an open environment, and the surveillance of known scenes for unauthorized access control.Source: Infrared physics & technology 49 (2007): 266–271. doi:10.1016/j.infrared.2006.06.028
DOI: 10.1016/j.infrared.2006.06.028

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2007 Part of book or chapter of book Unknown

Semi-automatic semantic tagging of 3D images from pancreas cells
Little S., Salvetti O., Perner P.
Detailed, consistent semantic annotation of large collections of multimedia data is difficult and time-consuming. In domains such as eScience, digital curation and industrial monitoring, fine-grained high-quality labeling of regions enables advanced semantic querying, analysis and aggregation and supports collaborative research. Manual annotation is inefficient and too subjective to be a viable solution. Automatic solutions are often highly domain or application specific, require large volumes of annotated training corpi and, if using a 'black box' approach, add little to the overall scientific knowledge. This article evaluates the use of simple artificial neural networks to semantically annotate micrographs and discusses the generic process chain necessary for semi-automatic semantic annotation of images.Source: MDA 2006/2007, edited by Petra Perner and Ovidio Salvetti, pp. 69–79, 2007

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2007 Book Unknown

Preface - Advances in mass data analysis of signals and images in medicine, biotechnology and chemistry
Perner P., Salvetti O.
The automatic analysis of images and signals in medicine, biotechnology, and chemistry is a challenging and demanding field. Signal-producing procedures by microscopes, spectrometers, and other sensors have found their way into wide fields of medicine, biotechnology, economy, and environmental analysis. With this arises the problem of the automatic mass analysis of signal information. Signal-interpreting systems which generate automatically the desired target statements from the signals are therefore of compelling necessity. The continuation of mass analyses on the basis of classical procedures leads to investments of proportions that are not feasible. New procedures and system architectures are therefore required. The scope of the International Conference on Mass Data Analysis of Images and Signals in Medicine, Biotechnology and Chemistry MDA (www.mda-signals.de) is to bring together researchers, practitioners, and industry people who are dealing with mass analysis of images and signals to present and discuss recent research in these fields.

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2007 Book Unknown

Editorial activity - Special Issue on Bayesian Source Separation
Kuruoglu E., Knuth K.
The signal processing problem known as source separation has rapidly grown in the last decade from being viewed as something of a curiosity to becoming a fundamental signal processing problem that is ubiquitous across scientific disciplines. Source separation problems are characterized by a set of sources that either emit or modulate signals that propagate to one or several detectors. The signal processing goal is to "separate" the recorded signals into the set of "source" signals. This basic situation appears in a wide variety of contexts ranging from the more traditional mixing of sound signals as in the Cocktail Party Problem to mixtures of source signals of spatial extent in images, such as in astrophysical applications where the objects of study are optically thin (transparent) or magnetic resonance imaging where the effects of several distinct processes are superimposed. At this point in time, source separation has been widely studied, resulting in an extensive array of source separation algorithms. Much of the effort has gone into developing what are known as blind source separation algorithms, referring to the fact that these algorithms are provided with a minimum amount of information about the nature of the recorded signals. These blind algorithms are extremely useful, as they are specifically designed to be generally applicable to a wide array of problems. Many of these techniques work well in a wide variety of situations, including those where noise is an issue.

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2007 Article Unknown

The TAU2 polyphonic music terminal. The project, its realisation and role in computer music
Bertini G.
The development of computer music carrying out at CNUCE and IEI, both CNR Institutes, in collaboration with L. Cherubini Conservatory of Music in Florence by a M° Pietro Grossi initiatives, are described. The ambitious goal was the construction of an audio terminal to interface like any peripheral device to the mainframe IBM 360/67 of the CNUCE, to allow the electronic production of sounds and the execution of polyphonic and polytimbric music in real time using the program TAUMUS. In the first part of the paper something about the experiments developed to use the new "electronic instrumentation"in music are introduced, citing also the state of the art and the problems encountered using the systems at the time. In the following, detailed solution adopted for TAU2 design and realization are described, in order to generate sounds by additive synthesis, avoiding performance in differed time (off-line). The definition and choice of how to use the system, the production of the pieces, interactions with the musicians, teaching and demonstrations with TAU2-TAUMUS, have combined to create an original musical environment that contributed notably to the development of musical informatics in Italy.Source: Musica tecnologia (Testo stamp.) 1 (2007): 339–366.

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2007 Article Unknown

A new measure on intuitionistic fuzzy set using Hausdorff metric and its application to edge detection
Tamalika C., Swades D., Salvetti O.
Intuitionistic fuzzy set (IFS) proposed by Attanassov has gained much importance to the researchers for its application in various fields such as pattern recognition. It takes into account the membership, non-membership function also another term hesitation degree. Hesitation degree is the lack of knowledge in assigning the membership function. In particular, the similarity measure between IFSs has increased its interest and several algorithms have been developed. In this paper a new method for measuring the distance between two intuitionistic fuzzy sets based on Hausdorff metric is proposed. The distance measure is the intuitionistic fuzzy divergence using Hausdorff metric. Our proposed method has been applied in image processing in detecting the edges of different kinds of practical images, demonstrating to be a tool for processing monochrome images.Source: International journal of fuzzy mathematics and systems 15 (2007): 1–16.

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2007 Article Unknown

CLeMUS - Computational Learning Methods for Unsupervised Segmentation
Salerno E., Wilson S.
An invited session on computational learning methods for unsupervised segmentation was held on 14 September in the framework of the 11th International Conference on Knowledge-Based and Intelligent Information & Engineering Systems (KES 2007) in Vietri sul Mare, Italy. This initiative was taken by the MUSCLE 'e-team' on unsupervised segmentation and classification of multichannel data. MUSCLE (Multimedia Understanding through Semantics, Computation and Learning) is a European network of excellence managed by ERCIM.Source: ERCIM news 71 (2007).

See at: ercim-news.ercim.org | CNR People


2007 Article Unknown

Sul modello per l'attività mentale proposto dalla Scuola Operativa Italiana
Beltrame R.
A model for the mental activity is discussed, that was proposed by Italian Operational School, and that describes the mental activity as a sequence of elementary activities without mutual connections.Source: Methodologia online WP 208 (2007): 1–6.

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2007 Article Unknown

The Theoretical Environment around 1965
Beltrame R.
This paper is part of the festschrift for Ernst von Glasersfeld, who has actively contributed to the development of the ideas of the Scuola Operativa Italiana (SOI) from 1947.The paper outlines the theoretical status of the SOI research around 1965, which also marks the conclusion of an important phase of this development.Source: Constructivist Foundations 2, 2-3 (2007): 25–28.

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2007 Conference object Unknown

Gen mikrodizi ifadeleri ve Kararli Dagilimlar (Microarray gene expression and stable laws)
Kuruoglu E. E., Salas D., Ruiz D. P.
In this work, we study the statistical distribution of microarray gene expression data. In particular, we give a brief review of literature pointing to the non-Gaussian features of gene expression data in the form of impulsiveness and asymmetry. We note that several previous publication note the Pareto tail behaviour in the data. We present a new model, namely the stable distribution to describe the observed statistical features of the data which is a subfamily of Pareto-tail distributions.Source: IEEE 15th Signal Processing and Communication Applications Conference, Eskisehir, Turkey, 11-13 June 2007
DOI: 10.1109/SIU.2007.4298832

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2007 Conference object Unknown

ISYREADET: un sistema integrato per il restauro virtuale di documenti antichi
Console E., Valerie B., Cazuguel G., Legnaioli S., Palleschi V., Tassone R., Tonazzini A.
Isyreadet (Integrated System for Recovering and Archiving Degraded Texts) is a research project funded by the European Commission whose aim has been to realize an integrated hardware and software system for the virtual restoring of damaged historical documents using innovative methods and tools, such as multispectral cameras and image processing algorithms. During the two years life of the project (2003-2004) the consortium, formed by five SMEs (T.E.A. s.a.s., Catanzaro, Art Conservation, Vlaardingen, Atelier Quillet, La Rochelle, Art Innovation, Hengelo, Transmedia Technology, Swansea) and three RTD Performers (CNR- Istituto per i Processi Chimico-Fisici, Pisa, CNR- Isituto di Scienza e Tecnologie dell'Informazione, Pisa, ENST- École Nationale Supérieure des Télécommunications, Brest), has successfully carried out a series of activities. The activities provided for the realization of the project have been related to the analysis and the classification of different kind of possible damages, the digitalization of the test documents using a multispectral camera, the selection of suitable image enhancement algorithms and further application, the implementation of the user-friendly graphic interface. Above are shown the outcomes reached by the application of the algorithms for the virtual restoration of the documents.Source: IV Convegno Nazionale A.I.Ar., pp. 903–913, Pisa, Italy, 1-3 febbraio 2006

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2007 Conference object Unknown

Gürültülü Astrofiziksel Görüntü Karışımlarının Kör Zaman-Sıklık Kaynak Ayrıştırma Yöntemleri ile Ayrıştırılmas = Separation of noisy astrophysical images by blind time-frequency source
Ozgen T., Kuruoglu E. E., Herranz D.
Two blind time-frequency source separation methods in the literature are adapted to astrophysical image mixtures and four algorithms are developed to separate them into their cosmic components; cosmic microwave background (CMB) radiation, galactic dust and synchrotron. These components simulated according to their physical models are mixed via realistic coefficients, and are subjected to simulated additive, nonstationary Gaussian noise components of realistic power levels, to yield image mixtures. The developed algorithms are compared with the FastICA algorithm and CMB component is found to be recovered with an improvement reaching to 3.16 decibels from CMB-synchrotron mixtures.Source: IEEE 15th Signal Processing and Communication Applications Conference, pp. 1264–1267, Eskisehir, Turkey, 11-13 June 2007
DOI: 10.1109/SIU.2007.4298795

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2007 Conference object Unknown

Intellectual system of diseases early detection on the basis of the computer analysis of erythrocytes electron images
Radievski V., Jaliabova N., Khachidze M., Radievski D., Gurevich I., Salvetti O.
The problem of the diseases early detection basing on the computer analysis and on the recognition of the form of the erythrocytes image is considered. The erythrocytes image processing is carried out, and the features, on the basis of which their recognition and, consequently, the diseases diagnostic are carried out, are distinguished. The algorithms of processing and recognition of erythrocytes image are developed.Source: Information Technologies in Control, pp. 265–269, Tbilisi, Georgia, 10-12 October 2007

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2007 Conference object Unknown

Intuitionistic Fuzzy C means algorithm in medical image segmentation
Chaira T., De S., Salvetti O.
This paper presents a novel intuitionistic fuzzy C means clustering method using intuitionistic fuzzy set theory. This clustering method has also been used for identification of mammogram cysts. In this method, the hesitation degree has been taken into account along with the membership degree, where the cluster centers may converge to a desirable location than the cluster centers obtained by fuzzy C means algorithm. Experimental results on mammogram images show the effectiveness of the proposed method in contrast to existing fuzzy C means algorithms.Source: International Conference on Advances in Pattern Recognition -I CAPR 2007, Kolkata, India, 2-4 January 2007

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2007 Conference object Open Access OPEN

Markov Zinciri Monte Carlo ile Tam Bayesçi Imge Ayrıstırma (Fully bayesian image separation using Markov chain Monte Carlo)
Kayabol K., Kuruoglu E. E., Sankur B.
In this study, we investigate the image separation problem under noisy environments. In the definition of the problem, the Bayesian approach is considered. We present a fully stochastic method based on Markov chain Monte Carlo (MCMC), instead of other deterministic methods, used in Bayesian image separation.Source: IEEE 15th Signal Processing and Communication Applications Conference, pp. 969–972, Eskisehir, Turkey, 11-13 June 2007
DOI: 10.1109/SIU.2007.4298796

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2007 Conference object Unknown

Nuclei images analysis: technology, diagnostic feature and experimental study
Gurevich I., Murashov D., Salvetti O., Niemann H.
The information technology for automated morphologic analysis of the cytological slides, taken from patients with the lymphatic system tumours, was developed. The main contributions of the paper are the technology, the set of features for representation of nuclei images in pattern recognition problems (automated diagnostics), and experimental study of the technology and the features informativeness. The main components of the technology are: acquisition of cytological slides, method for segmentation of nuclei in the cytological slides, synthesis of the feature based nuclei description for subsequent classification, nuclei image analysis based on pattern recognition and scale-space techniques. The experiments confirmed efficiency of the developed technology. The discussion of the obtained results is given. The developed technology is implemented in the software system.Source: 2nd International Conference on Computer Vision Theory and Applications, pp. 204–210, Barcelona, Spain, 8-11 March 2007

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2007 Conference object Unknown

Semi-automatic semantic annotation of images
Little S., Salvetti O., Perner P.
Detailed, consistent semantic annotation of large collections of multimedia data is difficult and time-consuming. In domains such as eScience, digital curation and industrial monitoring, finegrained high-quality labeling of regions enables advanced semantic querying, analysis and aggregation and supports collaborative research. Manual annotation is inefficient and too subjective to be a viable solution. Automatic solutions are often highly domain or application specific, require large volumes of annotated training corpi and, if using a 'black box' approach, add little to the overall scientific knowledge. This article evaluates the use of simple artificial neural networks to semantically annotate micrographs and discusses the generic process chain necessary for semi-automatic semantic annotation of images.Source: Workshop-Woche: Lernen-Wissen-Adaption. LWA 2007, pp. 113–118, Halle, Germany, 24-26 September 2007

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