Pattern Recognition and Image Analysis, Oct 1, 2015
Problems of composing a feature description and developing a comparison procedure for the images ... more Problems of composing a feature description and developing a comparison procedure for the images of paintings in attribution are considered. A feature description of a facture of paintings based on the characteristics of a grayscale image relief and elements of the structure tensor is proposed. In contrast to known techniques, the feature description is formed only by informative fragments of images and does not require preliminary segmentation of individual brushstrokes. Parameters of feature extraction procedures are chosen. Measures of dissimilarity between images of paintings are proposed. Computational experiments are carried out. The feature description proposed is a quantitative characteristic of the artistic style of an author. The procedure developed for comparing images can be applied together with other types of investigation of paintings to make an attributional conclusion.
... Vavilova 40, Moscow, GSP-1, 117968 Russia, Head of the Computer Science Laboratory Doctoral, ... more ... Vavilova 40, Moscow, GSP-1, 117968 Russia, Head of the Computer Science Laboratory Doctoral, igourevi@ccas.ru Andrei V. Khilkov ... Vavilova 40, Moscow, GSP-1, 117968 Russia, PhD Senior Researcher, smetanin@ccas.ru Yuri I. Zhuravlev Scientific Council on Cybernetics ...
In this paper, we considered a problem of detecting specific textural regions in digital images. ... more In this paper, we considered a problem of detecting specific textural regions in digital images. A task for detecting specific textural regions is addressed as a problem for segmenting textural images. We proposed a technique based on modified super-pixel segmentation algorithm with post-processing procedure. A vector image pixel description is augmented with texture features computed from structure tensor components. Augmented pixel description enables to take into account texture coherence and orientation as well as spatial and color properties of image regions. To obtain an acceptable segmentation quality, a minimum information criterion is used. A computational experiment involves artificial and real images. The developed technique is applied to images of paintings for localizing groups of brushstrokes. Results of the experiment show efficiency of the proposed technique.
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, May 9, 2019
In this paper, an algorithm for automated detecting diagnostic events in video channel of video a... more In this paper, an algorithm for automated detecting diagnostic events in video channel of video and electroencephalographic (EEG) monitoring data is presented. The analysis of video sequences is focused on identifying a group of frames with high or very low (depending on the type of seizure) dynamics of informative areas according to a criterion calculated during processing of the optical flow. The preliminary results of the analysis of real clinical data are given and compared with data obtained from the synchronous EEG. The results showed the possibility in principle of reliable diagnosing epileptic seizures and distinguishing them from nonepileptic events.
One of the problems solved by analyzing the data of long-term Video EEG monitoring is the differe... more One of the problems solved by analyzing the data of long-term Video EEG monitoring is the differentiation of epileptic and artifact events. For this, not only multichannel EEG signals are used, but also video data analysis, since traditional methods based on the analysis of EEG wavelet spectrograms cannot reliably distinguish an epileptic seizure from a chewing artifact. In this paper, we propose an algorithm for detecting artifact events based on a joint analysis of the level of the optical flow and the ridges of wavelet spectrograms. The preliminary results of the analysis of real clinical data are given. The results show the possibility in principle of reliable distinguishing nonepileptic events from epileptic seizures.
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
In this work, we propose a new algorithm for detecting the indicator of delayed cerebral ischemia... more In this work, we propose a new algorithm for detecting the indicator of delayed cerebral ischemia from video-EEG monitoring data. The proposed algorithm combines an algorithm for detecting the effect of interchannel time-frequency synchronization of wavelet spectrogram ridges of EEG signals and an algorithm for detecting motion artifacts in video recording frames. Using the EEG analysis algorithm, we identify an indicator that is used to predict the occurrence of ischemia. By analyzing the optical flow, we exclude time intervals in which erroneous fixation of ischemia indicators is possible. The developed algorithm was tested on the clinical data of video-EEG monitoring. The preliminary results obtained during testing confirm the fundamental possibility of detecting the ischemia indicators and the acceptable accuracy of detecting motion artifacts leading to an erroneous diagnosis.
In this paper, a problem of image segmentation quality is considered. The problem of segmentation... more In this paper, a problem of image segmentation quality is considered. The problem of segmentation quality is viewed as selecting the best segmentation from a set of images generated by segmentation algorithm at different parameter values. A technique for selecting the best segmented image is proposed. Information redundancy measure is used as a criterion for optimizing segmentation quality. It is shown that proposed method for constructing the redundancy measure gives the extremal properties. Computing experiment confirmed that the segmented image corresponding to a minimum of redundancy measure produces the suitable dissimilarity when compared with the original image. The segmented image which was selected using the proposed criterion, gives the highest similarity with the ground-truth segmentations, available in the database.The research was supported in part by the Russian Foundation for Basic Research (grants No 15-07-09324 and No 15-0104671)
В рамках разработки технологии обнаружения эпилептических приступов по данным видео-ЭЭГ мониторин... more В рамках разработки технологии обнаружения эпилептических приступов по данным видео-ЭЭГ мониторинга предлагается алгоритм автоматического обнаружения приступов у пациентов на основе анализа количественных характеристик мимики видеоизображений. Анализ видеопоследовательностей ориентирован на выявлении группы кадров (соответственно, временного интервала) с высокой динамикой отдельных областей по критерию, вычисляемому при обработке оптического потока. Приведены предварительные результаты анализа реальных клинических данных и определены требования к условиям видеосъемки. In this paper, an algorithm for automated detecting diagnostic events in video channel of video and electroencephalographic monitoring data is presented. The algorithm is based on the analysis of the quantitative features of facial expressions in images of video data. The analysis of video sequences is aimed on detecting a group of frames (and corresponding time interval) characterized by a high activity of frame regio...
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2021
The work is devoted to the study of the frequency features of the optical flow obtained from the ... more The work is devoted to the study of the frequency features of the optical flow obtained from the video record of long-term videoelectroencephalographic (video-EEG) monitoring data of patients with epilepsy. It is necessary to obtain features to recognize epileptic seizures and differentiate them from non-epileptic events. We propose to analyze the periodograms of the smoothed optical flow calculated from the fragments of the patient's video recordings. We use Welch's method to obtain periodograms. The values of the power spectral density of the optical flow at the selected frequencies will be used as features. Using the clustering algorithm, four groups of events were identified in video recordings.
Communications in Computer and Information Science, 2019
In this paper, the problem of image segmentation quality is considered. The main idea is to find ... more In this paper, the problem of image segmentation quality is considered. The main idea is to find a quality criterion, which could have an extremum. The problem is viewed as selecting the best segmentation from a set of images generated by segmentation algorithm at different parameter values. We propose to use information redundancy measure as a criterion for optimizing segmentation quality. The method for constructing the redundancy measure provides criterion with extremal properties. To show efficiency of the proposed criterion, computing experiment is carried out. The proposed criterion is combined with SLIC and EDISON segmentation algorithms. Computing experiment shows that the segmented image corresponding to a minimum of redundancy measure produces acceptable information distance when compared with the original image. In most cases, the lowest information distance between this segmented image and ground-truth segmentations is obtained. An example of applying the redundancy measure to segmentation of images of painting material cross-sections is considered.
2021 International Conference on Information Technology and Nanotechnology (ITNT), 2021
A method is proposed for the segmentation of long-term records of electroencephalograms into time... more A method is proposed for the segmentation of long-term records of electroencephalograms into time intervals that are significant in the diagnosis of epilepsy. The method is based on the analysis of EEG synchronization and power spectral density analysis using threshold methods.
In this work, the problem of threads counting in images of canvases of paintings is considered. C... more In this work, the problem of threads counting in images of canvases of paintings is considered. Counting of threads is necessary for measuring canvas density and a number of other parameters used by art historians for dating the artworks. We propose to use raking light in the image acquisition process in order to emphasize canvas texture. We modify and adapt known techniques developed for inspecting fabrics in the textile industry. Three threads counting algorithms based on filtering in the Fourier domain and thresholding techniques are proposed and tested. These algorithms for measuring the canvas density from images taken in raking light are efficient in cases when lead white has been used to create the painting, and the analysis of canvas images acquired in X-rays and transmitted light is ineffective. The results of the experiment show that the accuracy of the proposed threads counting algorithms is comparable to the accuracy of known techniques.
The developed system is a tool for high aperture imaging of the fundus. The obtained high resolut... more The developed system is a tool for high aperture imaging of the fundus. The obtained high resolution images preserve the topology of the blood vessels. The system is based on mosaicking a series of distinct low aperture fragments in order to obtain a high aperture image. Mosaicking is implemented by a neural network with stubborn learning taking into account the importance of the information of particular features. In mosaicking, the aberrations of the third order are partly compensated.
Proceedings of the V International conference Information Technology and Nanotechnology 2019, 2019
In this paper, a technique for automated detecting diagnostic events in the video channel of vide... more In this paper, a technique for automated detecting diagnostic events in the video channel of video and electroencephalographic monitoring data is presented. The technique is based on the analysis of the quantitative features of facial expressions in images of video data. The analysis of video sequences is aimed at detecting a group of frames characterized by high activity of frame regions. For detecting the frames, a criterion computed from the optical flow is proposed. The preliminary results of the analysis of real clinical data are presented. The intervals of synchronous muscle and brain activity, which may correspond to an epileptic seizure, are detected. These intervals can be used for diagnosing epileptic seizures and distinguishing them from non-epileptic events. Requirements for video shooting conditions are formulated.
Proceedings of the V International conference Information Technology and Nanotechnology 2019, 2019
In this paper, a new technique for detecting concealed objects in the images acquired by a passiv... more In this paper, a new technique for detecting concealed objects in the images acquired by a passive THz imaging system is proposed. The technique is based on a method for mutual information maximization successfully used for image matching. For reducing computational expenses, we propose to analyze the mutual information at local maxima of the crosscorrelation function computed in the Fourier domain. The proposed technique does not require parameter tuning. A computing experiment approved the efficiency of the proposed technique and the possibility of its implementation in security systems.
ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2019
In this paper, an algorithm for automated detecting diagnostic events in video channel of video a... more In this paper, an algorithm for automated detecting diagnostic events in video channel of video and electroencephalographic (EEG) monitoring data is presented. The analysis of video sequences is focused on identifying a group of frames with high or very low (depending on the type of seizure) dynamics of informative areas according to a criterion calculated during processing of the optical flow. The preliminary results of the analysis of real clinical data are given and compared with data obtained from the synchronous EEG. The results showed the possibility in principle of reliable diagnosing epileptic seizures and distinguishing them from nonepileptic events.
Pattern Recognition and Image Analysis, Oct 1, 2015
Problems of composing a feature description and developing a comparison procedure for the images ... more Problems of composing a feature description and developing a comparison procedure for the images of paintings in attribution are considered. A feature description of a facture of paintings based on the characteristics of a grayscale image relief and elements of the structure tensor is proposed. In contrast to known techniques, the feature description is formed only by informative fragments of images and does not require preliminary segmentation of individual brushstrokes. Parameters of feature extraction procedures are chosen. Measures of dissimilarity between images of paintings are proposed. Computational experiments are carried out. The feature description proposed is a quantitative characteristic of the artistic style of an author. The procedure developed for comparing images can be applied together with other types of investigation of paintings to make an attributional conclusion.
... Vavilova 40, Moscow, GSP-1, 117968 Russia, Head of the Computer Science Laboratory Doctoral, ... more ... Vavilova 40, Moscow, GSP-1, 117968 Russia, Head of the Computer Science Laboratory Doctoral, igourevi@ccas.ru Andrei V. Khilkov ... Vavilova 40, Moscow, GSP-1, 117968 Russia, PhD Senior Researcher, smetanin@ccas.ru Yuri I. Zhuravlev Scientific Council on Cybernetics ...
In this paper, we considered a problem of detecting specific textural regions in digital images. ... more In this paper, we considered a problem of detecting specific textural regions in digital images. A task for detecting specific textural regions is addressed as a problem for segmenting textural images. We proposed a technique based on modified super-pixel segmentation algorithm with post-processing procedure. A vector image pixel description is augmented with texture features computed from structure tensor components. Augmented pixel description enables to take into account texture coherence and orientation as well as spatial and color properties of image regions. To obtain an acceptable segmentation quality, a minimum information criterion is used. A computational experiment involves artificial and real images. The developed technique is applied to images of paintings for localizing groups of brushstrokes. Results of the experiment show efficiency of the proposed technique.
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, May 9, 2019
In this paper, an algorithm for automated detecting diagnostic events in video channel of video a... more In this paper, an algorithm for automated detecting diagnostic events in video channel of video and electroencephalographic (EEG) monitoring data is presented. The analysis of video sequences is focused on identifying a group of frames with high or very low (depending on the type of seizure) dynamics of informative areas according to a criterion calculated during processing of the optical flow. The preliminary results of the analysis of real clinical data are given and compared with data obtained from the synchronous EEG. The results showed the possibility in principle of reliable diagnosing epileptic seizures and distinguishing them from nonepileptic events.
One of the problems solved by analyzing the data of long-term Video EEG monitoring is the differe... more One of the problems solved by analyzing the data of long-term Video EEG monitoring is the differentiation of epileptic and artifact events. For this, not only multichannel EEG signals are used, but also video data analysis, since traditional methods based on the analysis of EEG wavelet spectrograms cannot reliably distinguish an epileptic seizure from a chewing artifact. In this paper, we propose an algorithm for detecting artifact events based on a joint analysis of the level of the optical flow and the ridges of wavelet spectrograms. The preliminary results of the analysis of real clinical data are given. The results show the possibility in principle of reliable distinguishing nonepileptic events from epileptic seizures.
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
In this work, we propose a new algorithm for detecting the indicator of delayed cerebral ischemia... more In this work, we propose a new algorithm for detecting the indicator of delayed cerebral ischemia from video-EEG monitoring data. The proposed algorithm combines an algorithm for detecting the effect of interchannel time-frequency synchronization of wavelet spectrogram ridges of EEG signals and an algorithm for detecting motion artifacts in video recording frames. Using the EEG analysis algorithm, we identify an indicator that is used to predict the occurrence of ischemia. By analyzing the optical flow, we exclude time intervals in which erroneous fixation of ischemia indicators is possible. The developed algorithm was tested on the clinical data of video-EEG monitoring. The preliminary results obtained during testing confirm the fundamental possibility of detecting the ischemia indicators and the acceptable accuracy of detecting motion artifacts leading to an erroneous diagnosis.
In this paper, a problem of image segmentation quality is considered. The problem of segmentation... more In this paper, a problem of image segmentation quality is considered. The problem of segmentation quality is viewed as selecting the best segmentation from a set of images generated by segmentation algorithm at different parameter values. A technique for selecting the best segmented image is proposed. Information redundancy measure is used as a criterion for optimizing segmentation quality. It is shown that proposed method for constructing the redundancy measure gives the extremal properties. Computing experiment confirmed that the segmented image corresponding to a minimum of redundancy measure produces the suitable dissimilarity when compared with the original image. The segmented image which was selected using the proposed criterion, gives the highest similarity with the ground-truth segmentations, available in the database.The research was supported in part by the Russian Foundation for Basic Research (grants No 15-07-09324 and No 15-0104671)
В рамках разработки технологии обнаружения эпилептических приступов по данным видео-ЭЭГ мониторин... more В рамках разработки технологии обнаружения эпилептических приступов по данным видео-ЭЭГ мониторинга предлагается алгоритм автоматического обнаружения приступов у пациентов на основе анализа количественных характеристик мимики видеоизображений. Анализ видеопоследовательностей ориентирован на выявлении группы кадров (соответственно, временного интервала) с высокой динамикой отдельных областей по критерию, вычисляемому при обработке оптического потока. Приведены предварительные результаты анализа реальных клинических данных и определены требования к условиям видеосъемки. In this paper, an algorithm for automated detecting diagnostic events in video channel of video and electroencephalographic monitoring data is presented. The algorithm is based on the analysis of the quantitative features of facial expressions in images of video data. The analysis of video sequences is aimed on detecting a group of frames (and corresponding time interval) characterized by a high activity of frame regio...
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2021
The work is devoted to the study of the frequency features of the optical flow obtained from the ... more The work is devoted to the study of the frequency features of the optical flow obtained from the video record of long-term videoelectroencephalographic (video-EEG) monitoring data of patients with epilepsy. It is necessary to obtain features to recognize epileptic seizures and differentiate them from non-epileptic events. We propose to analyze the periodograms of the smoothed optical flow calculated from the fragments of the patient's video recordings. We use Welch's method to obtain periodograms. The values of the power spectral density of the optical flow at the selected frequencies will be used as features. Using the clustering algorithm, four groups of events were identified in video recordings.
Communications in Computer and Information Science, 2019
In this paper, the problem of image segmentation quality is considered. The main idea is to find ... more In this paper, the problem of image segmentation quality is considered. The main idea is to find a quality criterion, which could have an extremum. The problem is viewed as selecting the best segmentation from a set of images generated by segmentation algorithm at different parameter values. We propose to use information redundancy measure as a criterion for optimizing segmentation quality. The method for constructing the redundancy measure provides criterion with extremal properties. To show efficiency of the proposed criterion, computing experiment is carried out. The proposed criterion is combined with SLIC and EDISON segmentation algorithms. Computing experiment shows that the segmented image corresponding to a minimum of redundancy measure produces acceptable information distance when compared with the original image. In most cases, the lowest information distance between this segmented image and ground-truth segmentations is obtained. An example of applying the redundancy measure to segmentation of images of painting material cross-sections is considered.
2021 International Conference on Information Technology and Nanotechnology (ITNT), 2021
A method is proposed for the segmentation of long-term records of electroencephalograms into time... more A method is proposed for the segmentation of long-term records of electroencephalograms into time intervals that are significant in the diagnosis of epilepsy. The method is based on the analysis of EEG synchronization and power spectral density analysis using threshold methods.
In this work, the problem of threads counting in images of canvases of paintings is considered. C... more In this work, the problem of threads counting in images of canvases of paintings is considered. Counting of threads is necessary for measuring canvas density and a number of other parameters used by art historians for dating the artworks. We propose to use raking light in the image acquisition process in order to emphasize canvas texture. We modify and adapt known techniques developed for inspecting fabrics in the textile industry. Three threads counting algorithms based on filtering in the Fourier domain and thresholding techniques are proposed and tested. These algorithms for measuring the canvas density from images taken in raking light are efficient in cases when lead white has been used to create the painting, and the analysis of canvas images acquired in X-rays and transmitted light is ineffective. The results of the experiment show that the accuracy of the proposed threads counting algorithms is comparable to the accuracy of known techniques.
The developed system is a tool for high aperture imaging of the fundus. The obtained high resolut... more The developed system is a tool for high aperture imaging of the fundus. The obtained high resolution images preserve the topology of the blood vessels. The system is based on mosaicking a series of distinct low aperture fragments in order to obtain a high aperture image. Mosaicking is implemented by a neural network with stubborn learning taking into account the importance of the information of particular features. In mosaicking, the aberrations of the third order are partly compensated.
Proceedings of the V International conference Information Technology and Nanotechnology 2019, 2019
In this paper, a technique for automated detecting diagnostic events in the video channel of vide... more In this paper, a technique for automated detecting diagnostic events in the video channel of video and electroencephalographic monitoring data is presented. The technique is based on the analysis of the quantitative features of facial expressions in images of video data. The analysis of video sequences is aimed at detecting a group of frames characterized by high activity of frame regions. For detecting the frames, a criterion computed from the optical flow is proposed. The preliminary results of the analysis of real clinical data are presented. The intervals of synchronous muscle and brain activity, which may correspond to an epileptic seizure, are detected. These intervals can be used for diagnosing epileptic seizures and distinguishing them from non-epileptic events. Requirements for video shooting conditions are formulated.
Proceedings of the V International conference Information Technology and Nanotechnology 2019, 2019
In this paper, a new technique for detecting concealed objects in the images acquired by a passiv... more In this paper, a new technique for detecting concealed objects in the images acquired by a passive THz imaging system is proposed. The technique is based on a method for mutual information maximization successfully used for image matching. For reducing computational expenses, we propose to analyze the mutual information at local maxima of the crosscorrelation function computed in the Fourier domain. The proposed technique does not require parameter tuning. A computing experiment approved the efficiency of the proposed technique and the possibility of its implementation in security systems.
ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2019
In this paper, an algorithm for automated detecting diagnostic events in video channel of video a... more In this paper, an algorithm for automated detecting diagnostic events in video channel of video and electroencephalographic (EEG) monitoring data is presented. The analysis of video sequences is focused on identifying a group of frames with high or very low (depending on the type of seizure) dynamics of informative areas according to a criterion calculated during processing of the optical flow. The preliminary results of the analysis of real clinical data are given and compared with data obtained from the synchronous EEG. The results showed the possibility in principle of reliable diagnosing epileptic seizures and distinguishing them from nonepileptic events.
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Papers by D. Murashov