2004
Journal article
Open Access
An IR image processing approach for characterising combustion instability
Chimenti M., Di Natali C., Mariotti G., Paganini E., Pieri G., Salvetti O.
"The paper presents a first approach to the analysis of the dynamic behaviour of a premixed hydrogen/air jet flame using near-IR imaging. In this kind of flames spectral lines are observed in the infrared, visible, and ultraviolet regions; emissions of visible light are however not so strong as in other wavelengths, especially in the near-infrared and infrared portions of the spectrum. Using a video camera, coupled with an optical filter, it is possible to capture images of the flame in a burner and then acquire sequences of images of the near-infrared emission during the combustion process. In this work, carried out in the frame of a collaboration between ENEL Produzione - Ricerca and ISTI - CNR, we propose a method suitable to process and analyse maps of near-infrared emissions in order to characterize the flame morphology and compute geometric and densitometric features useful to describe the combustion dynamics. The map of the emissions presents in some cases different unconnected sources with interesting distribution. In our analysis, we considered two different layers: the single images, as a distribution of near-IR emission, and the complete sequence of images in a dynamical evolution of the whole process."Source: Infrared physics & technology 46 (2004): 41–47. doi:10.1016/j.infrared.2004.03.007
DOI: 10.1016/j.infrared.2004.03.007
Metrics:
Chimenti M., Di Natali C., Mariotti G., Paganini E., Pieri G., Salvetti O.
"The paper presents a first approach to the analysis of the dynamic behaviour of a premixed hydrogen/air jet flame using near-IR imaging. In this kind of flames spectral lines are observed in the infrared, visible, and ultraviolet regions; emissions of visible light are however not so strong as in other wavelengths, especially in the near-infrared and infrared portions of the spectrum. Using a video camera, coupled with an optical filter, it is possible to capture images of the flame in a burner and then acquire sequences of images of the near-infrared emission during the combustion process. In this work, carried out in the frame of a collaboration between ENEL Produzione - Ricerca and ISTI - CNR, we propose a method suitable to process and analyse maps of near-infrared emissions in order to characterize the flame morphology and compute geometric and densitometric features useful to describe the combustion dynamics. The map of the emissions presents in some cases different unconnected sources with interesting distribution. In our analysis, we considered two different layers: the single images, as a distribution of near-IR emission, and the complete sequence of images in a dynamical evolution of the whole process."Source: Infrared physics & technology 46 (2004): 41–47. doi:10.1016/j.infrared.2004.03.007
DOI: 10.1016/j.infrared.2004.03.007
Metrics:
See at:
ISTI Repository 
| Infrared Physics & Technology 
| www.sciencedirect.com | CNR ExploRA
2004
Conference article
Unknown
An extended maximum likelihood approach for the robust blind separation of autocorrelated images from noisy mixtures
Gerace I., Cricco D., Tonazzini A.
In this paper we consider the problem of separating autocorrelated source images from linear mixtures with unknown coefficients, in presence of even significant noise. Assuming the statistical independence of the sources, we formulate the problem in a Bayesian estimation framework, and describe local correlation within the individual source images through the use of suitable Gibbs priors, accounting also for well-behaved edges in the images. Based on an extension of the Maximum Likelihood approach to ICA, we derive an algorithm for recovering the mixing matrix that makes the estimated sources fit the known properties of the original sources. The preliminary experimental results on synthetic mixtures showed that a significant robustness against noise, both stationary and non-stationary, can be achieved even by using generic autocorrelation models.Source: ICA 2004 - Independent Component Analysis and Blind Signal Separation: Fifth International Conference, pp. 954–961, Granada, Spain, 22-24 September
Gerace I., Cricco D., Tonazzini A.
In this paper we consider the problem of separating autocorrelated source images from linear mixtures with unknown coefficients, in presence of even significant noise. Assuming the statistical independence of the sources, we formulate the problem in a Bayesian estimation framework, and describe local correlation within the individual source images through the use of suitable Gibbs priors, accounting also for well-behaved edges in the images. Based on an extension of the Maximum Likelihood approach to ICA, we derive an algorithm for recovering the mixing matrix that makes the estimated sources fit the known properties of the original sources. The preliminary experimental results on synthetic mixtures showed that a significant robustness against noise, both stationary and non-stationary, can be achieved even by using generic autocorrelation models.Source: ICA 2004 - Independent Component Analysis and Blind Signal Separation: Fifth International Conference, pp. 954–961, Granada, Spain, 22-24 September
See at: CNR ExploRA
2004
Conference article
Unknown
Astrophysical image separation using particle filters
Costagli M., Kuruoglu E. E., Ahmed A.
In this work, we will confront the problem of source separation 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 perform blind source separation, assume noiseless models, and in the few cases when noise is taken into account assume Gaussianity and space-invariance. However, in the real scenario both the sources and the noise are space-varying. In this work, we present a novel technique, namely particle filtering, for the non-blind (Bayesian) solution of the source separation problem, in case of non-stationary sources and noise, by exploiting available a-priori information.Source: International Conference on Independent Component Analysis and Blind Signal Separation (ICA), pp. 930–937, Granada, Spagna, 22-24 September 2004
Costagli M., Kuruoglu E. E., Ahmed A.
In this work, we will confront the problem of source separation 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 perform blind source separation, assume noiseless models, and in the few cases when noise is taken into account assume Gaussianity and space-invariance. However, in the real scenario both the sources and the noise are space-varying. In this work, we present a novel technique, namely particle filtering, for the non-blind (Bayesian) solution of the source separation problem, in case of non-stationary sources and noise, by exploiting available a-priori information.Source: International Conference on Independent Component Analysis and Blind Signal Separation (ICA), pp. 930–937, Granada, Spagna, 22-24 September 2004
See at: CNR ExploRA
2004
Conference article
Unknown
Bleed-through removal from degraded documents using a color decorrelation method
Tonazzini A., Salerno E., Mochi M., Bedini L.
A color decorrelation strategy to improve the human or automatic readability of degraded documents is presented. The particular degradation that is considered here is bleed-through, that is, a pattern that interferes with the text to be read due to seeping of ink from the reverse side of the document. A simplified linear model for this degradation is introduced to permit the application of very fast decorrelation techniques to the RGB components of the color data images, and to compare this strategy to the independent component analysis approach. Some examples from an extensive experimentation with real ancient documents are described, and the possibility to further improve the restoration performance by using hyperspectral/multispectral data is envisaged.Source: International Workshop on Document Analysis Systems, pp. 229–240, Florence, Italy, 8-10 September
Tonazzini A., Salerno E., Mochi M., Bedini L.
A color decorrelation strategy to improve the human or automatic readability of degraded documents is presented. The particular degradation that is considered here is bleed-through, that is, a pattern that interferes with the text to be read due to seeping of ink from the reverse side of the document. A simplified linear model for this degradation is introduced to permit the application of very fast decorrelation techniques to the RGB components of the color data images, and to compare this strategy to the independent component analysis approach. Some examples from an extensive experimentation with real ancient documents are described, and the possibility to further improve the restoration performance by using hyperspectral/multispectral data is envisaged.Source: International Workshop on Document Analysis Systems, pp. 229–240, Florence, Italy, 8-10 September
See at: CNR ExploRA
2004
Conference article
Unknown
Blind source separation techniques for detecting hidden texts and textures in document images
Tonazzini A., Salerno E., Mochi M., Bedini L.
Blind Source Separation techniques, based both on Independent Component Analysis and on second order statistics, are presented and compared for extracting partially hidden texts and textures in document images. Barely perceivable features may occur, for instance, in ancient documents previously erased and then re-written (palimpsests), or for transparency or seeping of ink from the reverse side, or from watermarks in the paper. Detecting these features can be of great importance to scholars and historians. In our approach, the document is modeled as the superposition of a number of source patterns, and a simplified linear mixture model is introduced for describing the relationship between these sources and multispectral views of the document itself. The problem of detecting the patterns that are barely perceivable in the visible color image is thus formulated as the one of separating the various patterns in the mixtures. Some examples from an extensive experimentation with real ancient documents are shown and commented.Source: International Conference on Image Analysis and Recognition, pp. 241–248, Porto, Portugal, September
Tonazzini A., Salerno E., Mochi M., Bedini L.
Blind Source Separation techniques, based both on Independent Component Analysis and on second order statistics, are presented and compared for extracting partially hidden texts and textures in document images. Barely perceivable features may occur, for instance, in ancient documents previously erased and then re-written (palimpsests), or for transparency or seeping of ink from the reverse side, or from watermarks in the paper. Detecting these features can be of great importance to scholars and historians. In our approach, the document is modeled as the superposition of a number of source patterns, and a simplified linear mixture model is introduced for describing the relationship between these sources and multispectral views of the document itself. The problem of detecting the patterns that are barely perceivable in the visible color image is thus formulated as the one of separating the various patterns in the mixtures. Some examples from an extensive experimentation with real ancient documents are shown and commented.Source: International Conference on Image Analysis and Recognition, pp. 241–248, Porto, Portugal, September
See at: CNR ExploRA
2004
Journal article
Open Access
Extracting cosmic microwave background polarization from satellite astrophysical maps
Baccigalupi C., Perrotta F., De Zotti G., Smoot G. F., Burigana C., Maino D., Bedini L., Salerno E.
We present the application of the fast independent component analysis (FASTICA) technique for blind component separation to polarized astrophysical emission. We study how the cosmic microwave background (CMB) polarized signal, consisting of E and B modes, can be extracted from maps affected by substantial contamination from diffuse galactic foreground emission and instrumental noise. We implement Monte Carlo chains varying the CMB and noise realizations in order to assess the average capabilities of the algorithm and their variance. We perform the analysis of all-sky maps simulated according to the Planck satellite capabilities, modelling the sky signal as a superposition of teh CMB and of the existing simulated polarization templates of galactic synchrotron. Our results indicate that teh angular power spectrum of CMB E mode can be recovered an all scales up to l=1000, corresponding to the fourth acoustic oscillation, while the B-mode power spectrum can be detected, up to its turnover al l=100, if the ratio of tensor to scalar contributions to the temperature quadrupole exceeds 30 percent. The power spectrum of the cross-correlation between total intensity and polarization, TE, can be recovered up to l=1200, corresponding to the seventh TE acoustic oscillation.Source: Monthly notices of the Royal Astronomical Society (Print) 354 (2004): 55–70. doi:10.1111/j.1365-2966.2004.08168.x
DOI: 10.1111/j.1365-2966.2004.08168.x
DOI: 10.48550/arxiv.astro-ph/0209591
Metrics:
Baccigalupi C., Perrotta F., De Zotti G., Smoot G. F., Burigana C., Maino D., Bedini L., Salerno E.
We present the application of the fast independent component analysis (FASTICA) technique for blind component separation to polarized astrophysical emission. We study how the cosmic microwave background (CMB) polarized signal, consisting of E and B modes, can be extracted from maps affected by substantial contamination from diffuse galactic foreground emission and instrumental noise. We implement Monte Carlo chains varying the CMB and noise realizations in order to assess the average capabilities of the algorithm and their variance. We perform the analysis of all-sky maps simulated according to the Planck satellite capabilities, modelling the sky signal as a superposition of teh CMB and of the existing simulated polarization templates of galactic synchrotron. Our results indicate that teh angular power spectrum of CMB E mode can be recovered an all scales up to l=1000, corresponding to the fourth acoustic oscillation, while the B-mode power spectrum can be detected, up to its turnover al l=100, if the ratio of tensor to scalar contributions to the temperature quadrupole exceeds 30 percent. The power spectrum of the cross-correlation between total intensity and polarization, TE, can be recovered up to l=1200, corresponding to the seventh TE acoustic oscillation.Source: Monthly notices of the Royal Astronomical Society (Print) 354 (2004): 55–70. doi:10.1111/j.1365-2966.2004.08168.x
DOI: 10.1111/j.1365-2966.2004.08168.x
DOI: 10.48550/arxiv.astro-ph/0209591
Metrics:
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Monthly Notices of the Royal Astronomical Society | arXiv.org e-Print Archive | SISSA Digital Library | Monthly Notices of the Royal Astronomical Society | doi.org | CNR ExploRA
2004
Journal article
Restricted
Modeling SAR images with a generalization of the rayleigh distribution
Kuruoglu E. E., Zerubia J.
Synthetic aperture radar (SAR) imagery has found important applications due to its clear advantages over optical satellite imagery one of them being able to operate in various weather conditions. However, due to the physics of the radar imaging process, SAR images contain unwanted artifacts in the form of a granular look which is called speckle. The assumptions of the classical SAR image generation model lead to a Rayleigh distribution model for the histogram of the SAR image. However, some experimental data such as images of urban areas show impulsive characteristics that correspond to underlying heavytailed distributions, which are clearly nonRayleigh. Some alternative distributions have been suggested such as the Weibull, lognormal, and the kdistribution which had success in varying degrees depending on the application. Recently, an alternative model namely the stable distribution has been suggested for modeling radar clutter. In this paper, we show that the amplitude distribution of the complex wave, the real and the imaginery components of which are assumed to be distributed by the stable distribution, is a generalization of the Rayleigh distribution. We demonstrate that the amplitude distribution is a mixture of Rayleighs as is the k distribution in accordance with earlier work on modeling SAR images which showed that almost all successful SAR image models could be expressed as mixtures of Rayleighs. We also present parameter estimation techniques based on negative order moments for the new model. Finally, we test the performance of the model on urban images and compare with other models such as Rayleigh, Weibull, and the k distribution.Source: IEEE transactions on image processing 13 (2004): 527–533. doi:10.1109/TIP.2003.818017
DOI: 10.1109/tip.2003.818017
Metrics:
Kuruoglu E. E., Zerubia J.
Synthetic aperture radar (SAR) imagery has found important applications due to its clear advantages over optical satellite imagery one of them being able to operate in various weather conditions. However, due to the physics of the radar imaging process, SAR images contain unwanted artifacts in the form of a granular look which is called speckle. The assumptions of the classical SAR image generation model lead to a Rayleigh distribution model for the histogram of the SAR image. However, some experimental data such as images of urban areas show impulsive characteristics that correspond to underlying heavytailed distributions, which are clearly nonRayleigh. Some alternative distributions have been suggested such as the Weibull, lognormal, and the kdistribution which had success in varying degrees depending on the application. Recently, an alternative model namely the stable distribution has been suggested for modeling radar clutter. In this paper, we show that the amplitude distribution of the complex wave, the real and the imaginery components of which are assumed to be distributed by the stable distribution, is a generalization of the Rayleigh distribution. We demonstrate that the amplitude distribution is a mixture of Rayleighs as is the k distribution in accordance with earlier work on modeling SAR images which showed that almost all successful SAR image models could be expressed as mixtures of Rayleighs. We also present parameter estimation techniques based on negative order moments for the new model. Finally, we test the performance of the model on urban images and compare with other models such as Rayleigh, Weibull, and the k distribution.Source: IEEE transactions on image processing 13 (2004): 527–533. doi:10.1109/TIP.2003.818017
DOI: 10.1109/tip.2003.818017
Metrics:
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IEEE Transactions on Image Processing | ieeexplore.ieee.org | CNR ExploRA
2004
Conference article
Unknown
Source separation techniques applied to astrophysical maps
Salerno E., Tonazzini A., Kuruoglu E. E., Bedini L., Herranz D., Baccigalupi C.
This paper is a brief overview of our research on the separation of astrophysical microwave source maps from multichannel observations, utilising techniques ranging from fully blind source separation to Bayesian estimation. Each observed map is a mix of various source processes, such as the cosmic microwave background and other galactic and extragalactic emissions. Separating the individual sources from a set of observed maps is of great importance to astrophysicists. The individual emission spectra, which affect the mixing coefficients, are mostly unknown. For this reason, the solution of the separation problem requires ``blind'' techniques. To begin with, we tested classical fully blind methods, first assuming noiseless data, and then taking noise into account. Then, we further developed our approach by adopting generic source models and prior information about the mixing operator. We extended our formulation within a Bayesian framework so that prior information regarding the source map distributions and correlations can be incorporated. We assessed the different techniques on data sets simulating the ones expected by the forthcoming ESA's {em Planck Surveyor Satellite} mission.Source: Knowledge-Based Intelligent Information and Engineering Systems, pp. 426–432, Wellington NZ, 20-24 September
Salerno E., Tonazzini A., Kuruoglu E. E., Bedini L., Herranz D., Baccigalupi C.
This paper is a brief overview of our research on the separation of astrophysical microwave source maps from multichannel observations, utilising techniques ranging from fully blind source separation to Bayesian estimation. Each observed map is a mix of various source processes, such as the cosmic microwave background and other galactic and extragalactic emissions. Separating the individual sources from a set of observed maps is of great importance to astrophysicists. The individual emission spectra, which affect the mixing coefficients, are mostly unknown. For this reason, the solution of the separation problem requires ``blind'' techniques. To begin with, we tested classical fully blind methods, first assuming noiseless data, and then taking noise into account. Then, we further developed our approach by adopting generic source models and prior information about the mixing operator. We extended our formulation within a Bayesian framework so that prior information regarding the source map distributions and correlations can be incorporated. We assessed the different techniques on data sets simulating the ones expected by the forthcoming ESA's {em Planck Surveyor Satellite} mission.Source: Knowledge-Based Intelligent Information and Engineering Systems, pp. 426–432, Wellington NZ, 20-24 September
See at: CNR ExploRA
2004
Journal article
Open Access
Statistical analysis of IR thermographic sequences by PCA
S. Marinetti, E. Grinzato, P. G. Bison, E. Bozzi, M. Chimenti, G. Pieri, O. Salvetti
Automatic processing of IR sequences is a desirable target in Thermal Non Destructive Evaluation (TNDE) of materials. Unfortunately this task is made difficult by the presence of many undesired signals that corrupt the useful information detected by the IR camera. In this paper the Principal Component Analysis (PCA) is used to process IR image sequences to extract features and reduce redundancy by projecting the original data onto a system of orthogonal components. As a thermographic sequence contains information both in space and time, the way of applying PCA to these data cannot be straightforwardly borrowed from typical applications of PCA where the information is mainly spatial (e.g. Remote Sensing, Face Recognition). This peculiarity has been analysed and the results are reported. Finally, in addition to the use of PCA as an unsupervised method, its use in a 'learning and measuring' configuration is considered.Source: Infrared physics & technology 46 (2004): 85–91. doi:10.1016/j.infrared.2004.03.012
DOI: 10.1016/j.infrared.2004.03.012
Metrics:
S. Marinetti, E. Grinzato, P. G. Bison, E. Bozzi, M. Chimenti, G. Pieri, O. Salvetti
Automatic processing of IR sequences is a desirable target in Thermal Non Destructive Evaluation (TNDE) of materials. Unfortunately this task is made difficult by the presence of many undesired signals that corrupt the useful information detected by the IR camera. In this paper the Principal Component Analysis (PCA) is used to process IR image sequences to extract features and reduce redundancy by projecting the original data onto a system of orthogonal components. As a thermographic sequence contains information both in space and time, the way of applying PCA to these data cannot be straightforwardly borrowed from typical applications of PCA where the information is mainly spatial (e.g. Remote Sensing, Face Recognition). This peculiarity has been analysed and the results are reported. Finally, in addition to the use of PCA as an unsupervised method, its use in a 'learning and measuring' configuration is considered.Source: Infrared physics & technology 46 (2004): 85–91. doi:10.1016/j.infrared.2004.03.012
DOI: 10.1016/j.infrared.2004.03.012
Metrics:
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ISTI Repository | Infrared Physics & Technology | www.sciencedirect.com | CNR ExploRA
2004
Journal article
Open Access
An alpha-stable approach to the study of the P(D) distribution of unresolved point sources in CMB sky maps
Herranz D., Kuruoglu E. E., Toffolatti L.
We present a new approach to the statistical study and modelling of point source counts in astronomical images. The approach is based on the theory of alpha-stable distributions. We show that the non-Gaussian distribution of the intensity fluctuations produced by a generic point source population -- whose number counts follow a simple power law -- belongs to the alpha-stable family of distributions. Even if source counts do not follow a simple power law, we show that the alpha-stable model is still useful in many astrophysical scenarios. With the alpha-stable model it is possible to totally describe the non-Gaussian distribution with a few parameters which are closely related to the parameters describing the source counts, instead of an infinite number of moments. Using statistical tools available in the signal processing literature, we show how to estimate these parameters in an easy and fast way. Then we apply the method to Cosmic Microwave Background (CMB) observations where point sources appear as superimposed to the cosmological signal as well as the instrumental noise, and propose a method to statistically disentangle these contributions. In the case of the Planck mission, our technique is able to determine the parameters of the dominant point source populations with relative errors 5% for the 30 GHz and 857 GHz channels. The formalism and methods presented here can be useful also for experiments in other frequency ranges such as X-rays or radio Astronomy.Source: Astronomy & astrophysics (Print) 424 (2004): 1081–1096. doi:10.1051/0004-6361:20035858
DOI: 10.1051/0004-6361:20035858
DOI: 10.48550/arxiv.astro-ph/0307114
Metrics:
Herranz D., Kuruoglu E. E., Toffolatti L.
We present a new approach to the statistical study and modelling of point source counts in astronomical images. The approach is based on the theory of alpha-stable distributions. We show that the non-Gaussian distribution of the intensity fluctuations produced by a generic point source population -- whose number counts follow a simple power law -- belongs to the alpha-stable family of distributions. Even if source counts do not follow a simple power law, we show that the alpha-stable model is still useful in many astrophysical scenarios. With the alpha-stable model it is possible to totally describe the non-Gaussian distribution with a few parameters which are closely related to the parameters describing the source counts, instead of an infinite number of moments. Using statistical tools available in the signal processing literature, we show how to estimate these parameters in an easy and fast way. Then we apply the method to Cosmic Microwave Background (CMB) observations where point sources appear as superimposed to the cosmological signal as well as the instrumental noise, and propose a method to statistically disentangle these contributions. In the case of the Planck mission, our technique is able to determine the parameters of the dominant point source populations with relative errors 5% for the 30 GHz and 857 GHz channels. The formalism and methods presented here can be useful also for experiments in other frequency ranges such as X-rays or radio Astronomy.Source: Astronomy & astrophysics (Print) 424 (2004): 1081–1096. doi:10.1051/0004-6361:20035858
DOI: 10.1051/0004-6361:20035858
DOI: 10.48550/arxiv.astro-ph/0307114
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arXiv.org e-Print Archive | Astronomy and Astrophysics | Astronomy and Astrophysics | doi.org | www.aanda.org | CNR ExploRA
2004
Journal article
Unknown
Analysis and recognition of highly degraded printed characters
Tonazzini A., Vezzosi S., Bedini L.
This paper proposes an integrated system for the processing and analysis of highly degraded printed documents for the purpose of recognizing text characters. As a case study, ancient printed texts are considered. The system is comprised of various blocks operating sequentially. Starting with a single page of the document, the background noise is reduced by wavelet-based decomposition and filtering, the text lines are detected, extracted, and segmented by a simple and fast adaptive thresholding into blobs corresponding to characters, and the various blobs are analyzed by a feedforward multilayer neural network trained with a back-propagation algorithm. For each character, the probability associated with the recognition is then used as a discriminating parameter that determines the automatic activation of a feedback process, leading the system back to a block for refining segmentation. This block acts only on the small portions of the text where the recognition cannot be relied on and makes use of blind deconvolution and MRF-based segmentation techniques whose high complexity is greatly reduced when applied to a few subimages of small size. The experimental results highlight that the proposed system performs a very precise segmentation of the characters and then a highly effective recognition of even strongly degraded texts.Source: International journal on document analysis and recognition (Internet) 6 (2004): 236–247.
Tonazzini A., Vezzosi S., Bedini L.
This paper proposes an integrated system for the processing and analysis of highly degraded printed documents for the purpose of recognizing text characters. As a case study, ancient printed texts are considered. The system is comprised of various blocks operating sequentially. Starting with a single page of the document, the background noise is reduced by wavelet-based decomposition and filtering, the text lines are detected, extracted, and segmented by a simple and fast adaptive thresholding into blobs corresponding to characters, and the various blobs are analyzed by a feedforward multilayer neural network trained with a back-propagation algorithm. For each character, the probability associated with the recognition is then used as a discriminating parameter that determines the automatic activation of a feedback process, leading the system back to a block for refining segmentation. This block acts only on the small portions of the text where the recognition cannot be relied on and makes use of blind deconvolution and MRF-based segmentation techniques whose high complexity is greatly reduced when applied to a few subimages of small size. The experimental results highlight that the proposed system performs a very precise segmentation of the characters and then a highly effective recognition of even strongly degraded texts.Source: International journal on document analysis and recognition (Internet) 6 (2004): 236–247.
See at: CNR ExploRA
2004
Journal article
Restricted
A general automatic method for the analysis of NREM sleep microstructure
Barcaro U., Bonanni E., Maestri M., Murri L., Parrino L., Terzano M. G.
The NREM sleep EEG of 10 normal subjects was examined in order to recognize formal phasic events of sleep microstructure. The event identification was carried out following a three-step procedure: (1) computation of band-related descriptors derived from the EEG signal, (2) introduction of suitable thresholds and (3) application of simple logical principles, i.e. an exclusion principle and an overlapping principle.Source: Sleep medicine (Amsterdam. Print) 5 (2004): 567–576. doi:10.1016/j.sleep.2004.07.012
DOI: 10.1016/j.sleep.2004.07.012
Metrics:
Barcaro U., Bonanni E., Maestri M., Murri L., Parrino L., Terzano M. G.
The NREM sleep EEG of 10 normal subjects was examined in order to recognize formal phasic events of sleep microstructure. The event identification was carried out following a three-step procedure: (1) computation of band-related descriptors derived from the EEG signal, (2) introduction of suitable thresholds and (3) application of simple logical principles, i.e. an exclusion principle and an overlapping principle.Source: Sleep medicine (Amsterdam. Print) 5 (2004): 567–576. doi:10.1016/j.sleep.2004.07.012
DOI: 10.1016/j.sleep.2004.07.012
Metrics:
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Sleep Medicine | www.sciencedirect.com | CNR ExploRA
2004
Journal article
Unknown
Independent component analysis for document restoration
Tonazzini A., Bedini L., Salerno E.
We propose a novel approach to restoring digital document images, with the aim of improving text legibility and OCR performance. These are often compromised by the presence of artifacts in the background, derived from many kinds of degradations, such as spots, underwritings, and show-through or bleed-through effects. So far, background removal techniques have been based on local, adaptive filters and morphological-structural operators to cope with frequent low-contrast situations. For the specific problem of bleed-through/show-through, most work has been based on the comparison between the front and back pages. This, however, requires a preliminary registration of the two images. Our approach is based on viewing the problem as one of separating overlapped texts and then reformulating it as a blind source separation problem, approached through independent component analysis techniques. These methods have the advantage that no models are required for the background. In addition, we use the spectral components of the image at different bands, so that there is no need for registration. Examples of bleed-through cancellation and recovery of underwriting from palimpsests are provided.Source: International journal on document analysis and recognition (Internet) 7 (2004): 17–27.
Tonazzini A., Bedini L., Salerno E.
We propose a novel approach to restoring digital document images, with the aim of improving text legibility and OCR performance. These are often compromised by the presence of artifacts in the background, derived from many kinds of degradations, such as spots, underwritings, and show-through or bleed-through effects. So far, background removal techniques have been based on local, adaptive filters and morphological-structural operators to cope with frequent low-contrast situations. For the specific problem of bleed-through/show-through, most work has been based on the comparison between the front and back pages. This, however, requires a preliminary registration of the two images. Our approach is based on viewing the problem as one of separating overlapped texts and then reformulating it as a blind source separation problem, approached through independent component analysis techniques. These methods have the advantage that no models are required for the background. In addition, we use the spectral components of the image at different bands, so that there is no need for registration. Examples of bleed-through cancellation and recovery of underwriting from palimpsests are provided.Source: International journal on document analysis and recognition (Internet) 7 (2004): 17–27.
See at: CNR ExploRA
2004
Journal article
Unknown
A tool for system monitoring based on artificial neural networks
Di Bono M. G., Pieri G., Salvetti O.
A research has been carried out finalized to the definition of a methodology useful for the diagnosis and prediction of the correct evolution state of physical systems. In this paper we present a related model and a specific network topology for the considered problem. In particular, the prediction procedure is based on a 'Self Organizing Map'(SOM) and an 'Error Back-Propagation'(EBP) networks combined to form a hierarchical architecture. The network system has been developed and tested using data furnished by Alenia and consisting in sensorial data (FBG, Fiber Bragg Grating) and multi-format descriptive data regarding evaluation (SB). The obtained results have shown that the developed methodology is a promising tool for the diagnosis activity.Source: WSEAS transactions on systems 3 (2004): 746–751.
Di Bono M. G., Pieri G., Salvetti O.
A research has been carried out finalized to the definition of a methodology useful for the diagnosis and prediction of the correct evolution state of physical systems. In this paper we present a related model and a specific network topology for the considered problem. In particular, the prediction procedure is based on a 'Self Organizing Map'(SOM) and an 'Error Back-Propagation'(EBP) networks combined to form a hierarchical architecture. The network system has been developed and tested using data furnished by Alenia and consisting in sensorial data (FBG, Fiber Bragg Grating) and multi-format descriptive data regarding evaluation (SB). The obtained results have shown that the developed methodology is a promising tool for the diagnosis activity.Source: WSEAS transactions on systems 3 (2004): 746–751.
See at: CNR ExploRA
2004
Journal article
Unknown
Compressione di dati multi-spettrali mediante una procedura basata sull'analisi delle componenti principali
Bozzi E., Chimenti M., Galligani A., Pieri G., Salvetti O.
The paper describes an application of a procedure based on the Principal Components Analysis, used to process multi-variated data, obtained with different techniques. The paper reports the processing steps of a set of multi-spectral data, produced by the inspection in the visible range of a calibrated colour sample, using both the procedure and the standard algorithms to convert multi-spectral data into colour coordinates. The paper shows the correspondences and the differences between the results given by the different approaches.Source: Atti della Fondazione Giorgio Ronchi (1976) LIX (2004): 767–780.
Bozzi E., Chimenti M., Galligani A., Pieri G., Salvetti O.
The paper describes an application of a procedure based on the Principal Components Analysis, used to process multi-variated data, obtained with different techniques. The paper reports the processing steps of a set of multi-spectral data, produced by the inspection in the visible range of a calibrated colour sample, using both the procedure and the standard algorithms to convert multi-spectral data into colour coordinates. The paper shows the correspondences and the differences between the results given by the different approaches.Source: Atti della Fondazione Giorgio Ronchi (1976) LIX (2004): 767–780.
See at: CNR ExploRA
2004
Journal article
Unknown
Foraging strategies of breeding seabirds studied by bird-borne data loggers
Benvenuti S., Dall'Antonia L.
Our research group has devised and manufactured a data logger which glued on the back of a bird, can detect and memorise the direction in which the bird is heading during a flight. Given the birds' constant cruising speed, the memorised data can be used to recon-struct the whole flight path. Subsequent versions of this direction recorder, equipped with new sensors (depth meter and flight sensor), were used to investigate the foraging behaviour of several species of breeding marine birds (Balearic shearwater, Brünnich's guillemot, com-mon guillemot, razorbill, black-legged kittiwake, Audouin's gull, northern gannet, blue-foot-ed booby). The data recorded at different colony sites allowed us to identify the birds' feed-ing grounds and record the most relevant events occurring in the foraging trips, including the duration of the trips, total flight time, number and duration of the stops where feeding actual-ly occurred, dive profiles and diving behaviour. Differences in the foraging strategies between sexes and between incubating and brooding birds were also investigated.Source: Memoirs of National Institute of Polar Research. Special issue 58 (2004): 110–117.
Benvenuti S., Dall'Antonia L.
Our research group has devised and manufactured a data logger which glued on the back of a bird, can detect and memorise the direction in which the bird is heading during a flight. Given the birds' constant cruising speed, the memorised data can be used to recon-struct the whole flight path. Subsequent versions of this direction recorder, equipped with new sensors (depth meter and flight sensor), were used to investigate the foraging behaviour of several species of breeding marine birds (Balearic shearwater, Brünnich's guillemot, com-mon guillemot, razorbill, black-legged kittiwake, Audouin's gull, northern gannet, blue-foot-ed booby). The data recorded at different colony sites allowed us to identify the birds' feed-ing grounds and record the most relevant events occurring in the foraging trips, including the duration of the trips, total flight time, number and duration of the stops where feeding actual-ly occurred, dive profiles and diving behaviour. Differences in the foraging strategies between sexes and between incubating and brooding birds were also investigated.Source: Memoirs of National Institute of Polar Research. Special issue 58 (2004): 110–117.
See at: CNR ExploRA
2004
Journal article
Unknown
Interoperabilita' e multimedialita' come strategie di ottimizzazione dell'affidabilita' e di riduzione dei costi nell'ambito dei controlli non distruttivi in servizio
Borzacchiello G., Caturano G., Cavaccini G., Incarnato C., Albanese C., Gloria M., Kostakopoulos G., Minei G., Martinelli M., Salvetti O.
In seguito all'introduzione di avanzati ed innovativi criteri di progettazione, materiali e tecnologie di fabbricazione, i Controlli Non Distruttivi (CND) hanno acquisito un livello di complessità crescente. Tale complessità investe tutti gli aspetti dei CND: quelli più strettamente tecnologici (proliferazione di tecniche ispettive e di analisi), quelli procedurali (criteri di accettazione sempre più strutturati e sempre più orientati a metodologie di classificazione delle anomalie rivelate), quelli riguardanti la diversificazione delle figure professionali proprie del dominio e, soprattutto, quelli relativi alla grande mole di informazioni generate o comunque utilizzate nei processi di ispezione (procedure, specifiche, certificazioni, disegni, dati acquisiti, ecc.). In tale contesto, sta diventando sempre più difficile gestire un dominio così complesso senza ricorrere al supporto di tecnologie informatiche non tradizionali, cioè provenienti da settori quali Intelligenza Arificiale e Human Computer Interaction, che solo pochi anni fa erano relegati esclusivamente a contesti di ricerca: in questo lavoro vengono presentati i risultati - ottenuti nell'ambito del Progetto APEX di Alenia Aeronautica - relativi all'applicazione di tali tecnologie per l'ottimizzazione dell'affidabilità e la riduzione dei costi nei CND in servizio, per i quali le complessità prima citate sono ancor più esaltate da alcune specificità operative.Source: Il Giornale delle prove non distruttive, monitoraggio, diagnostica in fase di stampa (2004): 1–10.
Borzacchiello G., Caturano G., Cavaccini G., Incarnato C., Albanese C., Gloria M., Kostakopoulos G., Minei G., Martinelli M., Salvetti O.
In seguito all'introduzione di avanzati ed innovativi criteri di progettazione, materiali e tecnologie di fabbricazione, i Controlli Non Distruttivi (CND) hanno acquisito un livello di complessità crescente. Tale complessità investe tutti gli aspetti dei CND: quelli più strettamente tecnologici (proliferazione di tecniche ispettive e di analisi), quelli procedurali (criteri di accettazione sempre più strutturati e sempre più orientati a metodologie di classificazione delle anomalie rivelate), quelli riguardanti la diversificazione delle figure professionali proprie del dominio e, soprattutto, quelli relativi alla grande mole di informazioni generate o comunque utilizzate nei processi di ispezione (procedure, specifiche, certificazioni, disegni, dati acquisiti, ecc.). In tale contesto, sta diventando sempre più difficile gestire un dominio così complesso senza ricorrere al supporto di tecnologie informatiche non tradizionali, cioè provenienti da settori quali Intelligenza Arificiale e Human Computer Interaction, che solo pochi anni fa erano relegati esclusivamente a contesti di ricerca: in questo lavoro vengono presentati i risultati - ottenuti nell'ambito del Progetto APEX di Alenia Aeronautica - relativi all'applicazione di tali tecnologie per l'ottimizzazione dell'affidabilità e la riduzione dei costi nei CND in servizio, per i quali le complessità prima citate sono ancor più esaltate da alcune specificità operative.Source: Il Giornale delle prove non distruttive, monitoraggio, diagnostica in fase di stampa (2004): 1–10.
See at: CNR ExploRA
2004
Journal article
Open Access
Image analysis on the archimedes palimpsest
Tonazzini A., Bedini L., Salerno E.
Image processing procedures developed at ISTI-CNR have been applied to recover some of the hidden writing in the Archimedes palimpsest, an ancient manuscript in which faint remnants of several treatises by the great philosopher and mathematician are partially hidden under a more recent text.Source: ERCIM news 58 (2004): 53–54.
Tonazzini A., Bedini L., Salerno E.
Image processing procedures developed at ISTI-CNR have been applied to recover some of the hidden writing in the Archimedes palimpsest, an ancient manuscript in which faint remnants of several treatises by the great philosopher and mathematician are partially hidden under a more recent text.Source: ERCIM news 58 (2004): 53–54.
See at:
www.ercim.org | CNR ExploRA
2004
Conference article
Unknown
A 2-dimensional Wavelet based approach to recognise defects in C-scan maps
Bozzi E., Cavaccini G., Chimenti M., Di Bono M. G., Salvetti O.
An image processing procedure is proposed to detect porosity defects in composite materials, analyzing C-scan images obtained by ultrasound inspection techniques. An image described by a set of features is analyzed in order to evaluate its similarity with a reference set. A 2D wavelet transform is applied to the input image and then a feature extraction based on statistics of the detail images produced by the transform itself is performed. The Principal Component Analysis technique (PCA) is then applied in order to map input features into an output plane maximizing data variance. Finally the image is classified considering the distance between points in the PCA plane. This procedure is also applied for the analysis of a single image. Preliminary results on simulation images and real C-scan maps, show that the procedure is able to detect defects.Source: The 7h International Conference on Pattern Recognition and Image Analysis, pp. 627–630, St. Petersburg, 18-23 October 2004
Bozzi E., Cavaccini G., Chimenti M., Di Bono M. G., Salvetti O.
An image processing procedure is proposed to detect porosity defects in composite materials, analyzing C-scan images obtained by ultrasound inspection techniques. An image described by a set of features is analyzed in order to evaluate its similarity with a reference set. A 2D wavelet transform is applied to the input image and then a feature extraction based on statistics of the detail images produced by the transform itself is performed. The Principal Component Analysis technique (PCA) is then applied in order to map input features into an output plane maximizing data variance. Finally the image is classified considering the distance between points in the PCA plane. This procedure is also applied for the analysis of a single image. Preliminary results on simulation images and real C-scan maps, show that the procedure is able to detect defects.Source: The 7h International Conference on Pattern Recognition and Image Analysis, pp. 627–630, St. Petersburg, 18-23 October 2004
See at: CNR ExploRA
2004
Conference article
Unknown
Astrophysical image denoising using bivariate isotropic cauchy distributions in the undecimated wavelet domain
Achim A., Herranz D., Kuruoglu E. E.
Within the framework of wavelet analysis, we describe a novel technique for removing noise from astrophysical im- ages. We design a Bayesian estimator, which relies on a particular member of the family of isotropic ®-stable dis- tributions, namely the bivariate Cauchy density. Using the bivariate Cauchy model we develop a noise-removal pro- cessor that takes into account the interscale dependencies of wavelet coe±cients. We show through simulations that our proposed technique outperforms existing methods both visually and in terms of root mean squared error.Source: IEEE International Conference on Image Processing (ICIP), pp. 1225–1228, Singapore, 24-27 October 2004
Achim A., Herranz D., Kuruoglu E. E.
Within the framework of wavelet analysis, we describe a novel technique for removing noise from astrophysical im- ages. We design a Bayesian estimator, which relies on a particular member of the family of isotropic ®-stable dis- tributions, namely the bivariate Cauchy density. Using the bivariate Cauchy model we develop a noise-removal pro- cessor that takes into account the interscale dependencies of wavelet coe±cients. We show through simulations that our proposed technique outperforms existing methods both visually and in terms of root mean squared error.Source: IEEE International Conference on Image Processing (ICIP), pp. 1225–1228, Singapore, 24-27 October 2004
See at: CNR ExploRA