Informacja

Drogi użytkowniku, aplikacja do prawidłowego działania wymaga obsługi JavaScript. Proszę włącz obsługę JavaScript w Twojej przeglądarce.

English (EN)·Polski (PL)·Yкраїнський (UK)
Przejdź do strony domowej biblioteki Centralna Biblioteka Wojskowa Link otwiera się w nowym oknie Logo biblioteki Prolib Integro - strona głównaCentralna Biblioteka Wojskowa

Wyszukujesz frazę "pattern extraction" wg kryterium: Temat

  Lista filtrów
Wyrównaj
    Wyświetlanie 1-9 z 9
    Tytuł:
    Iris identification method using only a section of the pattern
    Autorzy:
    Bobulski, J.
    Powiązania:
    https://bibliotekanauki.pl/articles/174981.pdf
    Data publikacji:
    2018
    Wydawca:
    Politechnika Wrocławska. Oficyna Wydawnicza Politechniki Wrocławskiej
    Tematy:
    biometrics
    iris recognition
    iris pattern extraction
    Opis:
    Iris based authentication methods are popular due to their reliability and dependability. This paper proposes the method of the iris recognition that instead uses only two fragments of the pattern. The presented method allows for a simpler iris extraction, as it does not use a complex conversion of an iris pattern from a circular to rectangular shape. The results obtained from this experiment show similarities to other previous ones. Importantly, the proposed method may be treated as an alternative solution. The experiment confirmed the validity of the concept for the proposed iris recognition method. Moreover, this method is quicker in comparison to the others. The additional merit of the proposed solution is the elimination of the distortion which comes from the eyelids and eyelashes at the beginning of the iris image processing. Moreover, this method does not require using additional techniques to eliminate disturbances.
    Źródło:
    Optica Applicata; 2018, 48, 1; 149-160
    0078-5466
    1899-7015
    Pojawia się w:
    Optica Applicata
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Finger vein pattern extraction methods
    Metody ekstrakcji układu naczyniowego
    Autorzy:
    Waluś, M.
    Powiązania:
    https://bibliotekanauki.pl/articles/151327.pdf
    Data publikacji:
    2014
    Wydawca:
    Stowarzyszenie Inżynierów i Techników Mechaników Polskich
    Tematy:
    finger vein
    pattern extraction
    biometrics
    układ naczyniowy
    ekstrakcja cech
    biometria
    Opis:
    In this paper the author presents techniques used for finger vein pattern extraction from raw biometric images. The proposition of a new image acquisition system is given. The main conclusion is the usability of image enhancement during acquisition process before taking the snapshot of a biometric probe. The proposed solution, compared to other techniques, improves the image quality and the overall effectiveness of the biometric system in the context of proper identification or verification.
    W pracy przedstawiono metody wyodrębnienia wzorca układu naczyniowego palców dłoni z obrazów biometrycznych. Oprócz prezentacji najczęściej stosowanych metod przedstawiono prace autora w zakresie rozwoju nowego systemu akwizycji wzorców. W porównaniu do innych badań w tym zakresie skupiono się na zwiększeniu jakości obrazów poprzez lokalne dostrojenie jasności świecenia diod LED emitujących światło w zakresie widma bliskiej podczerwieni wykorzystywanych do oświetlenia palca w urządzeniu rejestrującym wzorce. Uzyskano obiecujące rezultaty polepszenia jakości obrazów głównie poprzez bardziej zróżnicowane uwidocznienie obszarów zajmowanych przez układ naczyniowy oraz pozostałe tkanki palca w porównaniu do innych metod. Obecnie trwają prace związane z ulepszeniem stworzonego prototypu urządzenia oraz prowadzone są konsultacje mające na celu określenie jego przydatność w diagnostyce medycznej.
    Źródło:
    Pomiary Automatyka Kontrola; 2014, R. 60, nr 6, 6; 366-368
    0032-4140
    Pojawia się w:
    Pomiary Automatyka Kontrola
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Determination of the Optimal Threshold Value and Number of Keypoints in Scale Invariant Feature Transform-based Copy-Move Forgery Detection
    Autorzy:
    Isnanto, R. Rizal
    Zahra, Ajub Ajulian
    Santoso, Imam
    Lubis, Muhammad Salman
    Powiązania:
    https://bibliotekanauki.pl/articles/227299.pdf
    Data publikacji:
    2020
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    forgery
    Gaussian noise
    feature extraction
    pattern matching
    Euclidean distance
    Opis:
    The copy-move forgery detection (CMFD) begins with the preprocessing until the image is ready to process. Then, the image features are extracted using a feature-transform-based extraction called the scale-invariant feature transform (SIFT). The last step is features matching using Generalized 2 Nearest-Neighbor (G2NN) method with threshold values variation. The problem is what is the optimal threshold value and number of keypoints so that copy-move detection has the highest accuracy. The optimal threshold value and number of keypoints had determined so that the detection n has the highest accuracy. The research was carried out on images without noise and with Gaussian noise.
    Źródło:
    International Journal of Electronics and Telecommunications; 2020, 66, 3; 561-569
    2300-1933
    Pojawia się w:
    International Journal of Electronics and Telecommunications
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Novel framework for aspect knowledge base generated automatically from social media using pattern rules
    Autorzy:
    Tran, Tuan Anh
    Duangsuwan, Jarunee
    Wettayaprasit, Wiphada
    Powiązania:
    https://bibliotekanauki.pl/articles/2097963.pdf
    Data publikacji:
    2021
    Wydawca:
    Akademia Górniczo-Hutnicza im. Stanisława Staszica w Krakowie. Wydawnictwo AGH
    Tematy:
    opinion mining
    aspect knowledge base
    aspect extraction
    pattern rules
    social media
    Opis:
    One of the factors that improve businesses in business intelligence is summarization systems that can generate summaries based on sentiment from social media. However, these systems cannot produce such summaries automatically; they use annotated datasets. To support these systems with annotated datasets, we propose a novel framework that uses pattern rules. The framework has two procedures: 1) pre-processing, and 2) aspect knowledge-base generation. The first procedure is to check and correct any misspelled words (bigram and unigram) by a proposed method and tag the parts-of-speech of all of the words. The second procedure is to automatically generate an aspect knowledge base that is to be used to produce sentiment summaries by sentiment-summarization systems. Pattern rules and semantic similarity-based pruning are used to automatically generate an aspect knowledge base from social media. In the experiments, eight domains from benchmark datasets of reviews are used. The performance evaluation of our proposed approach shows the highest performance when compared to other unsupervised approaches.
    Źródło:
    Computer Science; 2021, 22 (4); 489--516
    1508-2806
    2300-7036
    Pojawia się w:
    Computer Science
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Texture and gene expression analysis of the MRI brain in detection of Alzheimer’s disease
    Autorzy:
    Bustamam, A.
    Sarwinda, D.
    Ardenaswari, G.
    Powiązania:
    https://bibliotekanauki.pl/articles/91834.pdf
    Data publikacji:
    2018
    Wydawca:
    Społeczna Akademia Nauk w Łodzi. Polskie Towarzystwo Sieci Neuronowych
    Tematy:
    Alzheimer’s disease
    MRI
    Feature Extraction
    Bi-Clustering
    Local Binary Pattern
    LBP
    Opis:
    Alzheimer’s disease is a type of dementia that can cause problems with human memory, thinking and behavior. This disease causes cell death and nerve tissue damage in the brain. The brain damage can be detected using brain volume, whole brain form, and genetic testing. In this research, we propose texture analysis of the brain and genomic analysis to detect Alzheimer’s disease. 3D MRI images were chosen to analyze the texture of the brain, and microarray data were chosen to analyze gene expression. We classified Alzheimer’s disease into three types: Alzheimer’s, Mild Cognitive Impairment (MCI), and Normal. In this study, texture analysis was carried out by using the Advanced Local Binary Pattern (ALBP) and the Gray Level Co-occurrence Matrix (GLCM). We also propose the bi-clustering method to analyze microarray data. The experimental results from texture analysis show that ALBP had better performance than GLCM in classification of Alzheimer’s disease. The ALBP method achieved an average value of accuracy of between 75% - 100% for binary classification of the whole brain data. Furthermore, Biclustering method with microarray data shows good performance gene expression, where this information show influence Alzheimer’s disease with total of bi-cluster is 6.
    Źródło:
    Journal of Artificial Intelligence and Soft Computing Research; 2018, 8, 2; 111-120
    2083-2567
    2449-6499
    Pojawia się w:
    Journal of Artificial Intelligence and Soft Computing Research
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Critical exponent analysis applied to surface EMG signals for multifunction myoelectric control
    Autorzy:
    Phinyomark, A.
    Phothisonothai, M.
    Phukpattaranont, P.
    Limsakul, C.
    Powiązania:
    https://bibliotekanauki.pl/articles/220544.pdf
    Data publikacji:
    2011
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    biomedical signal processing
    electromyography signal
    feature extraction
    fractal analysis
    human machine interface
    pattern classification
    Opis:
    Based on recent advances in non-linear analysis, the surface electromyography (sEMG) signal has been studied from the viewpoints of self-affinity and complexity. In this study, we examine usage of critical exponent analysis (CE) method, a fractal dimension (FD) estimator, to study properties of the sEMG signal and to deploy these properties to characterize different movements for gesture recognition. SEMG signals were recorded from thirty subjects with seven hand movements and eight muscle channels. Mean values and coefficient of variations of the CE from all experiments show that there are larger variations between hand movement types but there is small variation within the same type. It also shows that the CE feature related to the self-affine property for the sEMG signal extracted from different activities is in the range of 1.855∼2.754. These results have also been evaluated by analysis-of-variance (p-value). Results show that the CE feature is more suitable to use as a learning parameter for a classifier compared with other representative features including root mean square, median frequency and Higuchi's method. Most p-values of the CE feature were less than 0.0001. Thus the FD that is computed by the CE method can be applied to be used as a feature for a wide variety of sEMG applications.
    Źródło:
    Metrology and Measurement Systems; 2011, 18, 4; 645-658
    0860-8229
    Pojawia się w:
    Metrology and Measurement Systems
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Rgb-D face recognition using LBP-DCT algorithm
    Autorzy:
    Kumar, Sunil B L
    Kumari, Sharmila M
    Powiązania:
    https://bibliotekanauki.pl/articles/1956066.pdf
    Data publikacji:
    2021
    Wydawca:
    Polskie Towarzystwo Promocji Wiedzy
    Tematy:
    RGB-D
    kinect
    local binary pattern
    pattern recognition
    feature extraction
    histogram
    face recognition
    lokalny wzorzec binarny
    rozpoznawanie wzorców
    wyodrębnianie cech
    rozpoznawanie twarzy
    Opis:
    Face recognition is one of the applications in image processing that recognizes or checks an individual's identity. 2D images are used to identify the face, but the problem is that this kind of image is very sensitive to changes in lighting and various angles of view. The images captured by 3D camera and stereo camera can also be used for recognition, but fairly long processing times is needed. RGB-D images that Kinect produces are used as a new alternative approach to 3D images. Such cameras cost less and can be used in any situation and any environment. This paper shows the face recognition algorithms’ performance using RGB-D images. These algorithms calculate the descriptor which uses RGB and Depth map faces based on local binary pattern. Those images are also tested for the fusion of LBP and DCT methods. The fusion of LBP and DCT approach produces a recognition rate of 97.5% during the experiment
    Źródło:
    Applied Computer Science; 2021, 17, 3; 73-81
    1895-3735
    Pojawia się w:
    Applied Computer Science
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Personal identification using retina
    Autorzy:
    Choraś, R.S.
    Powiązania:
    https://bibliotekanauki.pl/articles/333033.pdf
    Data publikacji:
    2009
    Wydawca:
    Uniwersytet Śląski. Wydział Informatyki i Nauki o Materiałach. Instytut Informatyki. Zakład Systemów Komputerowych
    Tematy:
    siatkówka
    biometria siatkówki
    wybór cech obrazu
    retina
    retina biometrics
    vessel pattern
    feature extraction
    Gabor transform
    feature vector
    matching
    Opis:
    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.
    Źródło:
    Journal of Medical Informatics & Technologies; 2009, 13; 53-58
    1642-6037
    Pojawia się w:
    Journal of Medical Informatics & Technologies
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Cortical pattern detection for the developing brain: a 3D vertex labeling and skeletonization approach
    Autorzy:
    Clouchoux, C.
    Kudelski, D.
    Bouyssi-Kobar, M.
    Viseur, S.
    du Plessis, A.
    Evans, A.
    Mari, J.-L.
    Limperopoulos, C.
    Powiązania:
    https://bibliotekanauki.pl/articles/333059.pdf
    Data publikacji:
    2010
    Wydawca:
    Uniwersytet Śląski. Wydział Informatyki i Nauki o Materiałach. Instytut Informatyki. Zakład Systemów Komputerowych
    Tematy:
    rozwój mózgu
    ocena krzywizny
    wychwytywanie cech
    sulcal pattern
    brain development
    in-vivo MRI
    cortical surface
    curvature estimation
    morphological operators
    feature extraction
    Opis:
    Normal brain development is associated with expansion and folding of the cerebral cortex in a normal sequence of gyral–sulcal formation. We propose a global approach for measuring the cortical folding pattern of the developing brain. Our method measures geometric features directly on the cortical surface mesh, based on vertex labeling and skeletonization. The resulting extraction provides an accurate representation of global cortical organization. We applied this method to 17 young infants in order to characterize the evolution of cortical organization in the developing brain.
    Źródło:
    Journal of Medical Informatics & Technologies; 2010, 16; 161-166
    1642-6037
    Pojawia się w:
    Journal of Medical Informatics & Technologies
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
      Wyświetlanie 1-9 z 9

      Ta witryna wykorzystuje pliki cookies do przechowywania informacji na Twoim komputerze. Pliki cookies stosujemy w celu świadczenia usług na najwyższym poziomie, w tym w sposób dostosowany do indywidualnych potrzeb. Korzystanie z witryny bez zmiany ustawień dotyczących cookies oznacza, że będą one zamieszczane w Twoim komputerze. W każdym momencie możesz dokonać zmiany ustawień dotyczących cookies