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1
Content available remote Stripe segmentation of oceanic internal waves in SAR images based on Gabor transform and K-means clustering
Qi Kai-Tuo, Zhang Hong-Sheng, Zheng Ying-Gang, Zhang Yu, Ding Long-Yu
Oceanologia
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2023
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Vol. 65 (4)
548--555
EN
Oceanic internal waves are an active ocean phenomenon that can be observed, and their relevant characteristics can be acquired using synthetic aperture radar (SAR). The locations of oceanic internal waves must be determined first to obtain the important parameters of oceanic internal waves from SAR images. An oceanic internal wave segmentation method with integrated light and dark stripes was described in this study. To extract the SAR image characteristics of oceanic internal waves, the Gabor transform was initially used, and then the K-means clustering algorithm was used to separate the light (dark) stripes of oceanic internal waves from the background in the SAR images. The regions of the dark (light) stripes were automatically determined based on the differences between the three classes, that is, the dark stripes, light stripes, and background area. Finally, the locations of the dark (light) stripes were determined by shifting a given distance along the normal direction of the long side with the minimum bounding rectangle of the light (dark) stripes. The best segmentation results were obtained based on the intersection over the union of the images, and the accuracy of segmentation was verified. Furthermore, the effectiveness and practicability of the proposed method in the light and dark stripe segmentation of SAR images of oceanic internal waves were illustrated. The proposed method prepares the foundation for future inversion studies of oceanic internal waves.
2
Content available remote Probabilistic principal component analysis-based dimensionality reduction and optimization for arrhythmia classification using ECG signals
Vishwanath Bhagyalakshmi, Pujeri Ramchandra Vittal, Devanagavi Geeta
Bio-Algorithms and Med-Systems
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2019
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Vol. 15, no. 1
art. no. 20180037
EN
Electrocardiogram (ECG) is an electrical signal that contains data about the state and functions of the heart and can be used to diagnose various types of arrhythmias effectively. The modeling and simulation of ECG under different conditions are significant to understand the function of the cardiovascular system and in the diagnosis of heart diseases. Arrhythmia is a severe peril to the patient recovering from acute myocardial infarction. The reliable detection of arrhythmia is a challenge for a cardiovascular diagnostic system. As a result, a considerable amount of research has focused on the development of algorithms for the accurate diagnosis of arrhythmias. In this paper, a system for the classification of arrhythmia is developed by employing the probabilistic principal component analysis (PPCA) model. Initially, the cluster head is selected for the effective transmission of ECG signals of patients using the adaptive fractional artificial bee colony algorithm, and multipath routing for transmission is selected using the fractional bee BAT algorithm. Features such as wavelet features, Gabor transform, empirical mode decomposition, and linear predictive coding features are extracted from the ECG signal with high dimension (which are reduced using PPCA) and finally given to the proposed classifier called adaptive genetic-bat (AGB) support vector neural network (which is trained using the AGB algorithm) for arrhythmia detection. The experimentation of the proposed system is done based on evaluation metrics, such as the number of alive nodes, normalized network energy, goodput, and accuracy. The proposed method obtained a classification accuracy of 0.9865 and a goodput of 0.0590 and provides a better classification of arrhythmia. The experimental results show that the proposed system is useful for the classification of arrhythmias, with a reasonably high accuracy of 0.9865 and a goodput of 0.0590. The validation of the proposed system offers acceptable results for clinical implementation.
3
Content available Voice recognition through the use of Gabor transform and heuristic algorithm
Woźniak M., Połap D.
International Journal of Electronics and Telecommunications
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2017
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Vol. 63, No. 2
159--164
EN
Increasingly popular use of verification methods based on specific characteristics of people like eyeball, fingerprint or voice makes inventing more accurate and irrefutable methods of that urgent. In this work we present voice verification based on Gabor transformation. Proposed approach involves creation of spectrogram, which serves as a habitat for the population in selected heuristic algorithm. The use of heuristic allows for feature extraction to enable identity verification using classical neural network. The results of the research are presented and discussed to show efficiency of the proposed methodology.
4
Content available Joint time-frequency and wavelet analysis - an introduction
Majkowski A., Kołodziej M., Rak R. J.
Metrology and Measurement Systems
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2014
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Vol. 21, nr 4
741--758
EN
A traditional frequency analysis is not appropriate for observation of properties of non-stationary signals. This stems from the fact that the time resolution is not defined in the Fourier spectrum. Thus, there is a need for methods implementing joint time-frequency analysis (t/f) algorithms. Practical aspects of some representative methods of time-frequency analysis, including Short Time Fourier Transform, Gabor Transform, Wigner-Ville Transform and Cone-Shaped Transform are described in this paper. Unfortunately, there is no correlation between the width of the time-frequency window and its frequency content in the t/f analysis. This property is not valid in the case of a wavelet transform. A wavelet is a wave-like oscillation, which forms its own “wavelet window”. Compression of the wavelet narrows the window, and vice versa. Individual wavelet functions are well localized in time and simultaneously in scale (the equivalent of frequency). The wavelet analysis owes its effectiveness to the pyramid algorithm described by Mallat, which enables fast decomposition of a signal into wavelet components.
5
Content available Infrared devices and techniques (revision)
Rogalski A., Chrzanowski K.
Metrology and Measurement Systems
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2014
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Vol. 21, nr 4
565--618
EN
The main objective of this paper is to produce an applications-oriented review covering infrared techniques and devices. At the beginning infrared systems fundamentals are presented with emphasis on thermal emission, scene radiation and contrast, cooling techniques, and optics. Special attention is focused on night vision and thermal imaging concepts. Next section concentrates shortly on selected infrared systems and is arranged in order to increase complexity; from image intensifier systems, thermal imaging systems, to space-based systems. In this section are also described active and passive smart weapon seekers. Finally, other important infrared techniques and devices are shortly described, among them being: non-contact thermometers, radiometers, LIDAR, and infrared gas sensors.
6
Content available A new form of Gabor Wigner Transform by adaptive thresholding in Gabor Transform and Wigner Distribution and the power of signal synthesis techniques to enhance the strengths of GWT
Ajab M., Taj I. A., Shafi I., Stankovic S.
Metrology and Measurement Systems
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2013
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Vol. 20, nr 1
99-106
EN
In this paper, a modified form of the Gabor Wigner Transform (GWT) has been proposed. It is based on adaptive thresholding in the Gabor Transform (GT) and Wigner Distribution (WD). The modified GWT combines the advantages of both GT and WD and proves itself as a powerful tool for analyzing multi-component signals. Performance analyses of the proposed distribution are tested on the examples, show high resolution and crossterms suppression. To exploit the strengths of GWT, the signal synthesis technique is used to extract amplitude varying auto-components of a multi-component signal. The proposed technique improves the readability of GWT and proves advantages of combined effects of these signal processing techniques.
7
Content available Pomiary i charakterystyka parasejsmicznych drgań gruntu w wybranym rejonie Rybnickiego Okręgu Węglowego
Lipski Z., Mrozek D.
Aparatura Badawcza i Dydaktyczna
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2013
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T. 18, nr 3
245-251
PL
W pracy przedstawiono wyniki analizy akcelerogramów będących obrazem drgań gruntu generowanych przez wstrząsy górnicze z rejonu Rydułtów w Rybnickim Okręgu Węglowym (ROW). Charakteryzują one obciążenia dynamiczne zabudowy i decydują o poziomie odpowiedzi dynamicznej konstrukcji nośnych budynków. W analizie wykorzystano transformację Gabora. Na jej podstawie obliczono wartości dwunastu zmiennych losowych, za pomocą których scharakteryzowane zostały własności czasowo-widmowe akcelerogramów. Analizowano 27 intensywnych wstrząsów górniczych. Uzyskane wyniki porównano z analogicznymi charakterystykami wstrząsów z rejonu Polkowic w Legnicko-Głogowskim Okręgu Miedziowym (LGOM). Ostatecznie sformułowano ocenę poziomu odpowiedzi dynamicznej budynków poddanych działaniu wstrząsów w rejonie Rydułtów.
EN
The article contains the results of the accelerations of the ground vibrations analysis, which were generated by mining quakes in the Rydułtowy region in Rybnik Coal District (ROW). They are characterized by the dynamic load building and determine of the level of dynamic response of the supporting structures of buildings. In the carried out analysis the Gabor transform was used. Then the twelve values of the random variables were calculated, whereby the property temporarily - spectral accelerations have been described. We analyzed 27 intensive mining quakes. The results were compared with the corresponding characteristics of the shocks from the region of Polkowice in Legnica - Głogów Copper District (LGOM). Finally, the assessment of the level of dynamic response of buildings subjected to quake in the Rydułtowy region were formulated.
8
Content available Comparative analysis of variants of Gabor-Wigner Transform for crossterm reduction
Ajab M., Taj I. A., Khan N. A.
Metrology and Measurement Systems
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2012
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Vol. 19, nr 3
499-508
EN
Gabor Wigner Transform (GWT) is a composition of two time-frequency planes (Gabor Transform (GT) and Wigner Distribution (WD)), and hence GWT takes the advantages of both transforms (high resolution of WD and cross-terms free GT). In multi-component signal analysis where GWT fails to extract auto-components, the marriage of signal processing and image processing techniques proved their potential to extract autocomponents. The proposed algorithm maintained the resolution of auto-components. This work also shows that the Fractional Fourier Transform (FRFT) domain is a powerful tool for signal analysis. Performance analysis of modified fractional GWT reveals that it provides a solution of cross-terms of WD and blurring of GT.
9
Content available Personal identification using retina
Choraś R.S.
Journal of Medical Informatics & Technologies
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2009
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Vol. 13
53--58
EN
This paper proposes a biometric system for authentication that uses the retina blood vessel pattern. The retina biometric analyzes the layer of blood vessels located at the back of the eye. The blood vessels at the back of the eye have a unique pattern, from eye to eye and person to person. The retina, a layer of blood vessels located at the back of the eye, forms an identity card for the individual under investigation. In particular retinal recognition creates an ”eye signature” from its vascular configuration and its artificial duplication is thought to be virtually impossible.
10
Content available remote Czasowo-częstotliwościowa analiza sygnałów (Encyklopedia Przeglądu Elektrotechnicznego)
Rak R.J., Majkowski A.
Przegląd Elektrotechniczny
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2004
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R. 80, nr 5
515-520
PL
Powszechnie wiadomo, że tradycyjna analiza częstotliwościowa nie nadaje się do obserwacji właściwości sygnałów niestacjonarnych. Rozdzielczość czasowa analizy dokonanej z pomocą tradycyjnej transformaty Fouriera, nie jest zadowalająca. Wymagana jest tutaj analiza wykorzystująca łączne czasowo-częstotliwościowe reprezentacje sygnałów. Rodzina reprezentacji czasowo-częstotliwościowych jest bardzo duża. W referacie przedstawiono praktyczne aspekty implementacji krótkoczasowej transformaty Fouriera, transformaty Gabora, Wignera-Ville'a oraz typu Cone-shaped.
EN
Traditional frequency analysis is not appropriate for the observation of properties of non-stationary signals. It is for the fact that the time resolution of the Fourier series representation is not very good. Thus, there is a need for an analysis implementing the joint time-frequency signal representations. The time-frequency representation family is very large. In this paper practical aspects of some representative methods are described including short time Fourier transform, Gabor transform, Wignera-Ville transform and Cone-shaped transform.
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