For marine sciences sometimes there is a need to perform underwater photography. Optical properti... more For marine sciences sometimes there is a need to perform underwater photography. Optical properties of light cause severe quality problems for underwater photography. Light of different energies is absorbed at highly different rates under water causing significant bluishness of the images. If the colour dependent attenuation under water can be properly estimated it should be possible to use computerised image processing to colour correct digital images using Beer’s Law.In this thesis we have developed such estimation and correction methods that have become progressively more complicated and more accurate giving successively better correction results. A process of estimation of downwelling attenuation coefficients from multi or hyper spectral data is a basis for automatic colour restoration of underwater taken images. The results indicate that for each diving site the unique and precise coefficients can be obtained.All standard digital cameras have built in white balancing and colour enhancement functions designed to make the images as aesthetically pleasing as possible. These functions can in most cameras not be switched off and the algorithms used are proprietary and undocumented. However, these enhancement functions can be estimated. Applying their reverse creates un-enhanced images and we show that our algorithms for underwater colour correction works significantly better when applied to such images.Finally, we have developed a method that uses point spectra from the spectrometer together with RGB colour images from a camera to generate pseudo-hyper-spectral images. Each of these can then be colour corrected. Finally, the images can be weighted together in the proportions needed to create new correct RGB images. This method is somewhat computationally demanding but gives very encouraging results.The algorithms and applications presented in this thesis show that automatic colour correction of underwater images can increase the credibility of data taken underwater for marine scientific purposes.
An adequate analysis of the originality of the video is of a great importance in video processing... more An adequate analysis of the originality of the video is of a great importance in video processing field. This paper presents a method for feature matching between two video streams. One of the video streams is subjected for severe compression, noise and rotation. These two copies represent the same movie but only one of the versions is original. Examples of reliable recognition of an original scene that is subjected for compression and noise are presented. The algorithm is invariant to image scale and rotation, providing robust matching across a substantial range of video signals. This paper shows an approach to using descriptive features for randomly chosen unstructured frames from video stream. By involving color information as a feature together with intensity profile for frame blocks we increase the robustness of the identification process. The median of low frequencies is measured, followed by an average of spectral information from the same frame to identify clusters belonging...
Abstract—For robots to plan their actions autonomously and interact with people, recognizing huma... more Abstract—For robots to plan their actions autonomously and interact with people, recognizing human emotions is crucial. For most humans nonverbal cues such as pitch, loudness, spectrum, speech rate are efficient carriers of emotions. The features of the sound of a spoken voice probably contains crucial information on the emotional state of the speaker, within this framework, a machine might use such properties of sound to recognize emotions. This work evaluated six different kinds of classifiers to predict six basic universal emotions from non-verbal features of human speech. The classification techniques used information from six audio files extracted from the eNTERFACE05 audio-visual emotion database. The information gain from a decision tree was also used in order to choose the most significant speech features, from a set of acoustic features commonly extracted in emotion analysis. The classifiers were evaluated with the proposed features and the features selected by the decision...
— Since second-order probability distributions assign probabilities to probabilities there is unc... more — Since second-order probability distributions assign probabilities to probabilities there is uncertainty on two levels. Although different types of uncertainty have been distinguished before and corresponding measures suggested, the distinction made here between first- and second-order levels of uncertainty has not been considered before. In this paper previously existing measures are considered from the perspective of first- and second-order uncertainty and new measures are introduced. We conclude that the concepts of uncertainty and informativeness needs to be qualified if used in a second-order probability context and suggest that from a certain point of view information can not be minimized, just shifted from one level to another. Index Terms—Uncertainty, entropy, second-order probability. I.
In attempting to address real-life decision problems, where uncertainty about input data prevails... more In attempting to address real-life decision problems, where uncertainty about input data prevails, some kind of representation of imprecise information is important and several have been proposed over the years. In par-ticular, first-order representations of imprecision, such as sets of probability measures, upper and lower prob-abilities, and interval probabilities and utilities of var-ious kinds, have been suggested for enabling a better representation of the input sentences. A common prob-lem is, however, that pure interval analyses in many cases cannot discriminate sufficiently between the var-ious strategies under consideration, which, needless to say, is a substantial problem in real-life decision making in agents as well as decision support tools. This is one reason prohibiting a more wide-spread use. In this arti-cle we demonstrate that in many situations, the discrim-ination can be made much clearer by using information inherent in the decision structure. It is discussed us...
DeÀn dà kllios C os _ an aÍtän kaÈ t ndoÔmena íti mlia C en poi¬ Pltwn, {TÐmaios} Abstract Adequa... more DeÀn dà kllios C os _ an aÍtän kaÈ t ndoÔmena íti mlia C en poi¬ Pltwn, {TÐmaios} Abstract Adequate representation of imprecise probabilities is a crucial and non-trivial problem in decision analysis. Second-order probability distributions is the model for imprecise probabilities whose merits are discussed in this thesis. That imprecise probabilities may be represented by second-order probability distributions is well known but there has been little attention to specific distributions. Since different probability distributions have different properties, the study of the desired properties of models of imprecise probabilities with respect to second-order models require analysis of particular second-order distributions. An often held objection to second-order probabilities is the apparent arbitrariness in the choice of distribution. We find some evidence that the structure of second-order distributions is an important factor that prohibits arbitrary choice of distributions. In particu...
Abstract: The inherent properties of water column usually affect underwater imagery by suppressin... more Abstract: The inherent properties of water column usually affect underwater imagery by suppressing high-energy wavelengths. One of the inherent properties, diffuse attenuation, can be estimated from multi or hyper spectral data and thus give information on how fast light of different wavelengths decreases with increasing depth. Based on exact depth measurements and data from a spectrometer incoming light on an object can be calculated and diffuse attenuation coefficient can be estimated. In this work the authors introduce a mathematical model that suggests the most stable wavelengths, which corresponds to estimated coefficients, based on spectral information from each depth. These values are then used in reconstruction of colours in underwater imagery. Since there are no digital hyper spectral cameras yet we are for the time being confined to point data, but the method is general and we show how it can be applied on multi spectral images. Key–Words: Water, Colour Correction, Spectra...
In real-life decision analysis, the probabilities and values of consequences are in general vague... more In real-life decision analysis, the probabilities and values of consequences are in general vague and imprecise. One way to model imprecise probabilities is to represent a probability with the interval between the lowest possible and the highest possible probability, respectively. However, there are disadvantages with this approach, one being that when an event has several possible outcomes, the distributions of belief in the different probabilities are heavily concentrated to their centers of mass, meaning that much of the information of the original intervals are lost. Representing an imprecise probability with the distribution’s center of mass therefore in practice gives much the same result as using an interval, but a single number instead of an interval is computationally easier and avoids problems such as overlapping intervals. Using this, we demonstrate why second-order calculations can add information when handling imprecise representations, as is the case of decision trees ...
In realistic decision problems there is more often than not uncertainty in the background informa... more In realistic decision problems there is more often than not uncertainty in the background information. As for representation of uncertain or imprecise probability values, second-order probability, i.e. probability distributions over probabilities, oers an option. With a subjective view of probability second-order probability would seem to be impractical since it is hard for a person to construct a second-order distribution that reects his or her beliefs. From the perspective of probability as relative frequency the task of constructing or updating a second-order probability distribution from data is somewhat easier. Here a very simple model for updating lower bounds of probabilities is employed. But the diculties in choosing second-order distributions may be further alleviated if structural properties are considered. Either some of the probability values are dependent in some way, e.g. that they are known to be almost equal, or they are not dependent in any other way than what follo...
Improvement of a Color Correction Algorithm for Underwater Images Through Compensating for Digita... more Improvement of a Color Correction Algorithm for Underwater Images Through Compensating for Digital Camera Behaviour
The inherent properties of water column usually affect underwater imagery by suppressing high-ene... more The inherent properties of water column usually affect underwater imagery by suppressing high-energy wavelengths. One of the inherent properties, diffuse attenuation, can be estimated from multi or hyper spectral data and thus give information on how fast light of different wavelengths decreases with increasing depth. Based on exact depth measurements and data from a spectrometer incoming light on an object can be calculated and diffuse attenuation coefficient can be estimated. In this work the authors introduce a mathematical model that suggests the most stable wavelengths, which corresponds to estimated coefficients, based on spectral information from each depth. These values are then used in reconstruction of colours in underwater imagery. Since there are no digital hyper spectral cameras yet we are for the time being confined to point data, but the method is general and we show how it can be applied on multi spectral images.
In explicatione consiliorum, maxima facere communis utilitas saepe trita ratio deligendi meliorem... more In explicatione consiliorum, maxima facere communis utilitas saepe trita ratio deligendi meliorem optionem est. Verum si probabilitates et utilitates incertae vel dubiae sint, communis utilitas p ...
We utilize second-order probability distributions for modeling second-order information over impr... more We utilize second-order probability distributions for modeling second-order information over imprecise evidence in the form of credal sets. We generalize the Dirichlet distribution to a shifted version, denoted the S-Dirichlet, which allows one to restrict the support of the distribution by lower bounds. Based on the S-Dirichlet distribution, we present a simple combination schema denoted as second-order credal combination (SOCC), which takes second-order probability into account. The combination schema is based on a set of particles, sampled from the operands, and a set of weights that are obtained through the S-Dirichlet distribution. We show by examples that the second-order probability distribution over the imprecise joint evidence can be remarkably concentrated and hence that the credal combination operator can significantly overestimate the imprecision.
The ultimate objective of studying, modeling and analyzing policy problems is to incorporate the ... more The ultimate objective of studying, modeling and analyzing policy problems is to incorporate the newest management technologies in the public policy decision-making in a meaningful and practically ...
For marine sciences sometimes there is a need to perform underwater photography. Optical properti... more For marine sciences sometimes there is a need to perform underwater photography. Optical properties of light cause severe quality problems for underwater photography. Light of different energies is absorbed at highly different rates under water causing significant bluishness of the images. If the colour dependent attenuation under water can be properly estimated it should be possible to use computerised image processing to colour correct digital images using Beer’s Law.In this thesis we have developed such estimation and correction methods that have become progressively more complicated and more accurate giving successively better correction results. A process of estimation of downwelling attenuation coefficients from multi or hyper spectral data is a basis for automatic colour restoration of underwater taken images. The results indicate that for each diving site the unique and precise coefficients can be obtained.All standard digital cameras have built in white balancing and colour enhancement functions designed to make the images as aesthetically pleasing as possible. These functions can in most cameras not be switched off and the algorithms used are proprietary and undocumented. However, these enhancement functions can be estimated. Applying their reverse creates un-enhanced images and we show that our algorithms for underwater colour correction works significantly better when applied to such images.Finally, we have developed a method that uses point spectra from the spectrometer together with RGB colour images from a camera to generate pseudo-hyper-spectral images. Each of these can then be colour corrected. Finally, the images can be weighted together in the proportions needed to create new correct RGB images. This method is somewhat computationally demanding but gives very encouraging results.The algorithms and applications presented in this thesis show that automatic colour correction of underwater images can increase the credibility of data taken underwater for marine scientific purposes.
An adequate analysis of the originality of the video is of a great importance in video processing... more An adequate analysis of the originality of the video is of a great importance in video processing field. This paper presents a method for feature matching between two video streams. One of the video streams is subjected for severe compression, noise and rotation. These two copies represent the same movie but only one of the versions is original. Examples of reliable recognition of an original scene that is subjected for compression and noise are presented. The algorithm is invariant to image scale and rotation, providing robust matching across a substantial range of video signals. This paper shows an approach to using descriptive features for randomly chosen unstructured frames from video stream. By involving color information as a feature together with intensity profile for frame blocks we increase the robustness of the identification process. The median of low frequencies is measured, followed by an average of spectral information from the same frame to identify clusters belonging...
Abstract—For robots to plan their actions autonomously and interact with people, recognizing huma... more Abstract—For robots to plan their actions autonomously and interact with people, recognizing human emotions is crucial. For most humans nonverbal cues such as pitch, loudness, spectrum, speech rate are efficient carriers of emotions. The features of the sound of a spoken voice probably contains crucial information on the emotional state of the speaker, within this framework, a machine might use such properties of sound to recognize emotions. This work evaluated six different kinds of classifiers to predict six basic universal emotions from non-verbal features of human speech. The classification techniques used information from six audio files extracted from the eNTERFACE05 audio-visual emotion database. The information gain from a decision tree was also used in order to choose the most significant speech features, from a set of acoustic features commonly extracted in emotion analysis. The classifiers were evaluated with the proposed features and the features selected by the decision...
— Since second-order probability distributions assign probabilities to probabilities there is unc... more — Since second-order probability distributions assign probabilities to probabilities there is uncertainty on two levels. Although different types of uncertainty have been distinguished before and corresponding measures suggested, the distinction made here between first- and second-order levels of uncertainty has not been considered before. In this paper previously existing measures are considered from the perspective of first- and second-order uncertainty and new measures are introduced. We conclude that the concepts of uncertainty and informativeness needs to be qualified if used in a second-order probability context and suggest that from a certain point of view information can not be minimized, just shifted from one level to another. Index Terms—Uncertainty, entropy, second-order probability. I.
In attempting to address real-life decision problems, where uncertainty about input data prevails... more In attempting to address real-life decision problems, where uncertainty about input data prevails, some kind of representation of imprecise information is important and several have been proposed over the years. In par-ticular, first-order representations of imprecision, such as sets of probability measures, upper and lower prob-abilities, and interval probabilities and utilities of var-ious kinds, have been suggested for enabling a better representation of the input sentences. A common prob-lem is, however, that pure interval analyses in many cases cannot discriminate sufficiently between the var-ious strategies under consideration, which, needless to say, is a substantial problem in real-life decision making in agents as well as decision support tools. This is one reason prohibiting a more wide-spread use. In this arti-cle we demonstrate that in many situations, the discrim-ination can be made much clearer by using information inherent in the decision structure. It is discussed us...
DeÀn dà kllios C os _ an aÍtän kaÈ t ndoÔmena íti mlia C en poi¬ Pltwn, {TÐmaios} Abstract Adequa... more DeÀn dà kllios C os _ an aÍtän kaÈ t ndoÔmena íti mlia C en poi¬ Pltwn, {TÐmaios} Abstract Adequate representation of imprecise probabilities is a crucial and non-trivial problem in decision analysis. Second-order probability distributions is the model for imprecise probabilities whose merits are discussed in this thesis. That imprecise probabilities may be represented by second-order probability distributions is well known but there has been little attention to specific distributions. Since different probability distributions have different properties, the study of the desired properties of models of imprecise probabilities with respect to second-order models require analysis of particular second-order distributions. An often held objection to second-order probabilities is the apparent arbitrariness in the choice of distribution. We find some evidence that the structure of second-order distributions is an important factor that prohibits arbitrary choice of distributions. In particu...
Abstract: The inherent properties of water column usually affect underwater imagery by suppressin... more Abstract: The inherent properties of water column usually affect underwater imagery by suppressing high-energy wavelengths. One of the inherent properties, diffuse attenuation, can be estimated from multi or hyper spectral data and thus give information on how fast light of different wavelengths decreases with increasing depth. Based on exact depth measurements and data from a spectrometer incoming light on an object can be calculated and diffuse attenuation coefficient can be estimated. In this work the authors introduce a mathematical model that suggests the most stable wavelengths, which corresponds to estimated coefficients, based on spectral information from each depth. These values are then used in reconstruction of colours in underwater imagery. Since there are no digital hyper spectral cameras yet we are for the time being confined to point data, but the method is general and we show how it can be applied on multi spectral images. Key–Words: Water, Colour Correction, Spectra...
In real-life decision analysis, the probabilities and values of consequences are in general vague... more In real-life decision analysis, the probabilities and values of consequences are in general vague and imprecise. One way to model imprecise probabilities is to represent a probability with the interval between the lowest possible and the highest possible probability, respectively. However, there are disadvantages with this approach, one being that when an event has several possible outcomes, the distributions of belief in the different probabilities are heavily concentrated to their centers of mass, meaning that much of the information of the original intervals are lost. Representing an imprecise probability with the distribution’s center of mass therefore in practice gives much the same result as using an interval, but a single number instead of an interval is computationally easier and avoids problems such as overlapping intervals. Using this, we demonstrate why second-order calculations can add information when handling imprecise representations, as is the case of decision trees ...
In realistic decision problems there is more often than not uncertainty in the background informa... more In realistic decision problems there is more often than not uncertainty in the background information. As for representation of uncertain or imprecise probability values, second-order probability, i.e. probability distributions over probabilities, oers an option. With a subjective view of probability second-order probability would seem to be impractical since it is hard for a person to construct a second-order distribution that reects his or her beliefs. From the perspective of probability as relative frequency the task of constructing or updating a second-order probability distribution from data is somewhat easier. Here a very simple model for updating lower bounds of probabilities is employed. But the diculties in choosing second-order distributions may be further alleviated if structural properties are considered. Either some of the probability values are dependent in some way, e.g. that they are known to be almost equal, or they are not dependent in any other way than what follo...
Improvement of a Color Correction Algorithm for Underwater Images Through Compensating for Digita... more Improvement of a Color Correction Algorithm for Underwater Images Through Compensating for Digital Camera Behaviour
The inherent properties of water column usually affect underwater imagery by suppressing high-ene... more The inherent properties of water column usually affect underwater imagery by suppressing high-energy wavelengths. One of the inherent properties, diffuse attenuation, can be estimated from multi or hyper spectral data and thus give information on how fast light of different wavelengths decreases with increasing depth. Based on exact depth measurements and data from a spectrometer incoming light on an object can be calculated and diffuse attenuation coefficient can be estimated. In this work the authors introduce a mathematical model that suggests the most stable wavelengths, which corresponds to estimated coefficients, based on spectral information from each depth. These values are then used in reconstruction of colours in underwater imagery. Since there are no digital hyper spectral cameras yet we are for the time being confined to point data, but the method is general and we show how it can be applied on multi spectral images.
In explicatione consiliorum, maxima facere communis utilitas saepe trita ratio deligendi meliorem... more In explicatione consiliorum, maxima facere communis utilitas saepe trita ratio deligendi meliorem optionem est. Verum si probabilitates et utilitates incertae vel dubiae sint, communis utilitas p ...
We utilize second-order probability distributions for modeling second-order information over impr... more We utilize second-order probability distributions for modeling second-order information over imprecise evidence in the form of credal sets. We generalize the Dirichlet distribution to a shifted version, denoted the S-Dirichlet, which allows one to restrict the support of the distribution by lower bounds. Based on the S-Dirichlet distribution, we present a simple combination schema denoted as second-order credal combination (SOCC), which takes second-order probability into account. The combination schema is based on a set of particles, sampled from the operands, and a set of weights that are obtained through the S-Dirichlet distribution. We show by examples that the second-order probability distribution over the imprecise joint evidence can be remarkably concentrated and hence that the credal combination operator can significantly overestimate the imprecision.
The ultimate objective of studying, modeling and analyzing policy problems is to incorporate the ... more The ultimate objective of studying, modeling and analyzing policy problems is to incorporate the newest management technologies in the public policy decision-making in a meaningful and practically ...
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