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    Wyświetlanie 1-14 z 14
    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:
    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:
    Opis i implementacja algorytmu wyznaczania rozkładu fazy obrazów prążkowych w układzie FPGA
    Hardware implementation of phase extraction algorithm in fringe pattern analysis
    Autorzy:
    Staszek, K.
    Powiązania:
    https://bibliotekanauki.pl/articles/155308.pdf
    Data publikacji:
    2012
    Wydawca:
    Stowarzyszenie Inżynierów i Techników Mechaników Polskich
    Tematy:
    obraz prążkowy
    ekstrakcja fazy
    transformacja falkowa
    FPGA
    fringe pattern
    phase extraction
    wavelet transform
    Opis:
    Niniejszy artykuł przedstawia opis algorytmu wyznaczania rozkładu fazy z obrazów prążkowych. Jest to jeden z kroków przetwarzania obrazów stosowanych powszechnie w profilometrii optycznej, dzięki której na podstawie zdjęcia można odtworzyć trójwymiarowy kształt obiektu. Algorytm oparty został na zespolonej transformacji falkowej i pozwala na pełną automatyzację procesu skanowania. Duży nacisk został położony na optymalizację pod kątem sprzętowej implementacji w układzie FPGA. Wykazana została dobra odporność zarówno na szumy jak i niską jakość obrazu prążkowego.
    This paper presents a phase extraction algorithm used in fringe pattern analysis. It is one of steps in optical profilometry process used to obtain full three-dimensional information about the measured object shape. The algorithm is based on the complex wavelet transform and allows full automation of the process. Since the fringe patterns represent non-stationary signals, application of time-frequency analysis provides better results than the commonly used Fourier transform. Six variants of the wavelet transform (one- and two-dimensional) were simulated in order to minimise the required hardware resources in FPGA and test their robustness. As a result the one-dimensional minimised transform of variable size was chosen. A further part of the paper is focused on particular blocks of implementation. The presented wavelet coefficient computational method decreases the number of necessary operations during transform computing and enables significant reducing of memory requirements. The applied arcus tangens block with logarithmic division of approximation intervals gives correct extracted phase values in the entire four-quarter interval. The solution mentioned above leads to great minimisation of the described block without any impact on the accuracy. The last part of the paper presents processing results. The emphasis was put on the noise robustness and influence of the fringe pattern poor quality on the processing error. As it is shown, the algorithm works correctly even with only three gray levels and high noise level present in the input picture.
    Źródło:
    Pomiary Automatyka Kontrola; 2012, R. 58, nr 3, 3; 298-301
    0032-4140
    Pojawia się w:
    Pomiary Automatyka Kontrola
    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:
    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:
    The epidemiological pattern of oroantral communication – a retrospective study
    Autorzy:
    Pawlik, Patrycja
    Stanek, Anna
    Wyganowska-Świątkowska, Marzena
    Błochowiak, Katarzyna
    Powiązania:
    https://bibliotekanauki.pl/articles/454686.pdf
    Data publikacji:
    2019
    Wydawca:
    Uniwersytet Rzeszowski. Wydawnictwo Uniwersytetu Rzeszowskiego
    Tematy:
    maxillary sinus
    oroantral communication
    tooth extraction
    Opis:
    Introduction. Oroantral communication (OAC) between the maxillary sinus and the oral cavity is an infrequent post-surgical complication occurring most commonly after extraction of posterior maxillary teeth. Aim. To present the characteristics of OAC and predisposing factors as well as evaluate postoperative pharmacological therapy and complications in patients with an OAC. Material and methods. In this retrospective study, medical records of 63 patients with diagnosed OAC between 2011 and 2018 were analyzed. Results. The most frequent causes for tooth extraction leading to an OAC were periodontitis (n=34; 54%), carious destruction of the tooth (n=14; 22.2%), and tooth impaction (n=10; 16%). First molars (n=28; 44.4%), second molars (n=14; 22.2%) and third molars (n= 13; 20.6%) were the most frequently related teeth to OACs. The majority of OACs appeared in the fourth (n=22; 35%) and third (n=20; 31.7%) decades of life. Conclusion. OACs are rarely seen on an everyday basis by general practitioners; however, if left untreated, they may lead to further serious complications. Proper postoperative precautions must be taken in order to prevent further complications, and thus the evaluation of predisposing factors is of great importance.
    Źródło:
    European Journal of Clinical and Experimental Medicine; 2019, 1; 38-44
    2544-2406
    2544-1361
    Pojawia się w:
    European Journal of Clinical and Experimental Medicine
    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:
    Wyznaczanie atrybutów sygnału EEG w oparciu o transformatę Stockwella
    EEG signal attribute extraction based on the Stockwell transform
    Autorzy:
    Rutkowski, G.
    Patan, K.
    Powiązania:
    https://bibliotekanauki.pl/articles/156767.pdf
    Data publikacji:
    2013
    Wydawca:
    Stowarzyszenie Inżynierów i Techników Mechaników Polskich
    Tematy:
    EEG
    reprezentacja czasowo-częstotliwościowa
    klasyfikacja
    S-transform
    pattern recognition
    classification
    Opis:
    W nowoczesnych systemach medycznych w dziedzinie elektroencefalografii coraz bardziej zwiększa się nacisk na udoskonalanie aparatury pomiarowej. Nieustannie poszukuje się rozwiązań poprawiających niedoskonałości sprzętowe, a trudności dotyczą zarówno sfery konstrukcyjnej, jak i zaimplementowanych algorytmów. Problemy dotyczą eliminacji artefaktów i samej charakterystyki sygnałów EEG. Proponowane rozwiązania począwszy od metod klasycznych, a skończywszy na metodach opartych na sztucznej inteligencji ciągle ewoluują i pozwalają na wdrażanie coraz to nowszych rozwiązań na potrzeby kliniczne. Techniki oparte na analizie widmowej pozwalają wspomóc pracę lekarzy specjalistów w procesie diagnostycznym dla poszczególnych dysfunkcji o podłożu neurologicznym. Jednym ze stosowanych rozwiązań jest dynamicznie rozwijająca się metodologia oparta na zaawansowanych narzędziach analizy widmowej. Transformata S pozwala na wprowadzenie i zastosowanie funkcji okna o zmiennej szerokości zależnej od częstotliwości. Uzyskane informacje pozwalają zarówno określić rozdzielczość zależną od częstotliwości, jak i wyznaczyć widmo. W artykule opisano eksperyment na próbkach rzeczywistych pomiarów EEG zgromadzonych przy ścisłej współpracy z Oddziałem Neurologii i Udarów Szpitala Wojewódzkiego w Zielonej Górze. Zaprezentowano wyniki przy użyciu transformaty S w ekstrakcji cech i klasyfikacji zaburzeń neurologicznych dla przypadków napadów epileptycznych.
    In modern medical systems more and more emphasis is put on improvement of the measuring equipment. We are constantly looking for solutions to improve both hardware and software. The main problems relate to the elimination of artifacts and the analysis of EEG signal characteristics. To date elaborated solutions still evolve and allow for the implementation of still newer and newer solutions for clinical needs. One of possible solutions is to use a dynamically developing methodology based on advanced spectral analysis tools. First, the Fourier Transform was used, but it turned out to be effective only for stationary signals. The Fourier Transform allows extracting information about the signal spectrum components, without providing the information about the component occurrence time of the component. Unfortunately, EEG signals are non-stationary in nature. The solution may be S Transform, which can be viewed as an extension of the popular Short-Time Fourier Transform and wavelet transform. S Transform allows for the introduction and application of window functions with a variable width frequency dependent. The resulting information helps us to determine attributes of EEG signals needed for classification. The paper deals with experiments carried out using EEG samples collected in close collaboration with the Ward of Neurology and Strokes of Provincial Hospital of Zielona Góra. EEG signals were recorded using 16-channel equipment under the supervision of experts in neurology practices. In result, 1154 sequences were acquired including both dysfunctions (586 epileptic seizures) and normal records (568). EEG sequences were analyzed using S-transform to extract signal features. The last step was classification of EEG signals performed using a nearest neighbor classifier. The presented results are very promising and may have an impact on the improvement and refinement of medical diagnostic tools.
    Źródło:
    Pomiary Automatyka Kontrola; 2013, R. 59, nr 3, 3; 208-211
    0032-4140
    Pojawia się w:
    Pomiary Automatyka Kontrola
    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:
    Recognition of Sign Language from High Resolution Images Using Adaptive Feature Extraction and Classification
    Autorzy:
    Csóka, Filip
    Polec, Jaroslav
    Csóka, Tibor
    Kačur, Juraj
    Powiązania:
    https://bibliotekanauki.pl/articles/226004.pdf
    Data publikacji:
    2019
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    sign language
    gesture
    sign
    recognition
    CNN
    LoG
    real-time
    pattern recognition
    machine learning
    Opis:
    A variety of algorithms allows gesture recognition in video sequences. Alleviating the need for interpreters is of interest to hearing impaired people, since it allows a great degree of self-sufficiency in communicating their intent to the non-sign language speakers without the need for interpreters. State-of-the-art in currently used algorithms in this domain is capable of either real-time recognition of sign language in low resolution videos or non-real-time recognition in high-resolution videos. This paper proposes a novel approach to real-time recognition of fingerspelling alphabet letters of American Sign Language (ASL) in ultra-high-resolution (UHD) video sequences. The proposed approach is based on adaptive Laplacian of Gaussian (LoG) filtering with local extrema detection using Features from Accelerated Segment Test (FAST) algorithm classified by a Convolutional Neural Network (CNN). The recognition rate of our algorithm was verified on real-life data.
    Źródło:
    International Journal of Electronics and Telecommunications; 2019, 65, 2; 303-308
    2300-1933
    Pojawia się w:
    International Journal of Electronics and Telecommunications
    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
    Tytuł:
    Pattern Recognition Methods for Detecting Voltage Sag Disturbances and Electromagnetic Interference in Smart Grids
    Autorzy:
    Yalcin, T.
    Ozdemir, M.
    Powiązania:
    https://bibliotekanauki.pl/articles/136160.pdf
    Data publikacji:
    2016
    Wydawca:
    EEEIC International Barbara Leonowicz Szabłowska
    Tematy:
    C4.5 decision trees
    electromagnetic interference
    feature extraction
    hilbert huang transform
    power quality disturbance
    smart grids
    support vector machines
    Opis:
    Identification of system disturbances, detection of them guarantees smart grids power quality (PQ) system reliability and provides long lasting life of the power system. The key goal of this study is to find the best accuracy of identification algorithm for non-stationary, non-linear power quality disturbances such as voltage sag, electromagnetic interference in smart grids. PQube, power quality and energy monitor, was used to acquire these distortions. Ensemble Empirical Mode Decomposition is used for electromagnetic interference reduction with first intrinsic mode function. Hilbert Huang Transform is used for generating instantaneous amplitude and instantaneous frequency feature of real time voltage sag power signal. Outputs of Hilbert Huang Transform is intrinsic mode functions (IMFs), instantaneous frequency (IF), and instantaneous amplitude (IA). Characteristic features are obtained from first IMFs, IF, and IA. The six features—, the mean, standard deviation,skewness, kurtosis of both IF and IA are then calculated. These features are normalized along with the inputs classifiers. The proposed power system monitoring system is able to detect power system voltage sag disturbances and capable of recognize electromagnetic interference component. In this study based on experimental studies, Hilbert Huang Transform based pattern recognition technique was used to investigate power signal to diagnose voltage sag and in power grid. Support Vector Machines and C4.5 Decision Tree were operated and their achievements were matched for precision and CPU timing. According to the analysis, decision tree algorithm without dimensionality reduction produces the best solution.
    Źródło:
    Transactions on Environment and Electrical Engineering; 2016, 1, 3; 86-93
    2450-5730
    Pojawia się w:
    Transactions on Environment and Electrical Engineering
    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
      Wyświetlanie 1-14 z 14

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