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    Wyświetlanie 1-5 z 5
    Tytuł:
    Local correlation and entropy maps as tools for detecting defects in industrial images
    Autorzy:
    Skubalska-Rafajłowicz, E.
    Powiązania:
    https://bibliotekanauki.pl/articles/908047.pdf
    Data publikacji:
    2008
    Wydawca:
    Uniwersytet Zielonogórski. Oficyna Wydawnicza
    Tematy:
    wykrywanie uszkodzenia
    przetwarzanie obrazu
    korelacja lokalna
    defects detection
    image processing
    local correlation
    entropy map
    Opis:
    The aim of this paper is to propose two methods of detecting defects in industrial products by an analysis of gray level images with low contrast between the defects and their background. An additional difficulty is the high nonuniformity of the background in different parts of the same image. The first method is based on correlating subimages with a nondefective reference subimage and searching for pixels with low correlation. To speed up calculations, correlations are replaced by a map of locally computed inner products. The second approach does not require a reference subimage and is based on estimating local entropies and searching for areas with maximum entropy. A nonparametric estimator of local entropy is also proposed, together with its realization as a bank of RBF neural networks. The performance of both methods is illustrated with an industrial image.
    Źródło:
    International Journal of Applied Mathematics and Computer Science; 2008, 18, 1; 41-47
    1641-876X
    2083-8492
    Pojawia się w:
    International Journal of Applied Mathematics and Computer Science
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Image processing for old movies by filters with motion detection
    Autorzy:
    Skonieczny, S.
    Powiązania:
    https://bibliotekanauki.pl/articles/908449.pdf
    Data publikacji:
    2005
    Wydawca:
    Uniwersytet Zielonogórski. Oficyna Wydawnicza
    Tematy:
    filtracja sekwencji obrazu
    detekcja ruchu
    stary film
    image sequence filtering
    motion detection
    old movie
    Opis:
    Old movies suffer from various types of degradation: severe noise, blurred edges of objects (low contrast), scratches, spots, etc. Finding an efficient denoising method is one of the most important and one of the oldest problems in image sequence processing. The crucial thing in image sequences is motion. If the motion is insignificant, then any motion noncompensated method of filtering can be applied. However, if the noise is significant, then this approach gives most often unsatisfactory results. In order to increase the quality of frames, motion compensated filters are usually applied. This is a very time consuming and awkward approach due to serious limitations of optical flow methods. In this paper, a review of various filters with motion detection when applied to the processing of image sequences coming from old movies is presented. These filters are nonlinear and based on the concept of multistage median filtering or mathematical morphology. Some new filters are proposed. The idea of these new filters presented here is to detect moving areas instead of performing full estimation of motion in the sequence and to apply exclusively 2D filters in those regions while applying 3D motion noncompensated filters in static areas, which usually significantly reduces the computational burden.
    Źródło:
    International Journal of Applied Mathematics and Computer Science; 2005, 15, 4; 481-491
    1641-876X
    2083-8492
    Pojawia się w:
    International Journal of Applied Mathematics and Computer Science
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Infrared small-target detection under a complex background based on a local gradient contrast method
    Autorzy:
    Yang, Linna
    Xie, Tao
    Liu, Mingxing
    Zhang, Mingjiang
    Qi, Shuaihui
    Yang, Jungang
    Powiązania:
    https://bibliotekanauki.pl/articles/2201024.pdf
    Data publikacji:
    2023
    Wydawca:
    Uniwersytet Zielonogórski. Oficyna Wydawnicza
    Tematy:
    small target detection
    local gradient contrast
    visual saliency
    infrared image processing
    kontrast lokalny
    wyróżnienie wizualne
    obrazowanie w podczerwieni
    Opis:
    Small target detection under a complex background has always been a hot and difficult problem in the field of image processing. Due to the factors such as a complex background and a low signal-to-noise ratio, the existing methods cannot robustly detect targets submerged in strong clutter and noise. In this paper, a local gradient contrast method (LGCM) is proposed. Firstly, the optimal scale for each pixel is obtained by calculating a multiscale salient map. Then, a subblockbased local gradient measure is designed; it can suppress strong clutter interference and pixel-sized noise simultaneously. Thirdly, the subblock-based local gradient measure and the salient map are utilized to construct the LGCM. Finally, an adaptive threshold is employed to extract the final detection result. Experimental results on six datasets demonstrate that the proposed method can discard clutters and yield superior results compared with state-of-the-art methods.
    Źródło:
    International Journal of Applied Mathematics and Computer Science; 2023, 33, 1; 33--43
    1641-876X
    2083-8492
    Pojawia się w:
    International Journal of Applied Mathematics and Computer Science
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Hand gesture recognition based on free-form contours and probabilistic inference
    Autorzy:
    Kasprzak, W.
    Wilkowski, A.
    Czapnik, K.
    Powiązania:
    https://bibliotekanauki.pl/articles/331308.pdf
    Data publikacji:
    2012
    Wydawca:
    Uniwersytet Zielonogórski. Oficyna Wydawnicza
    Tematy:
    śledzenie dłoni
    analiza sekwencji obrazów
    wnioskowanie stochastyczne
    active contours
    hand pose detection
    hand tracking
    image sequence analysis
    stochastic inference
    Opis:
    A computer vision system is described that captures color image sequences, detects and recognizes static hand poses (i.e., 'letters') and interprets pose sequences in terms of gestures (i.e., 'words'). The hand object is detected with a double-active contour-based method. A tracking of the hand pose in a short sequence allows detecting 'modified poses', like diacritic letters in national alphabets. The static hand pose set corresponds to hand signs of a thumb alphabet. Finally, by tracking hand poses in a longer image sequence, the pose sequence is interpreted in terms of gestures. Dynamic Bayesian models and their inference methods (particle filter and Viterbi search) are applied at this stage, allowing a bi-driven control of the entire system.
    Źródło:
    International Journal of Applied Mathematics and Computer Science; 2012, 22, 2; 437-448
    1641-876X
    2083-8492
    Pojawia się w:
    International Journal of Applied Mathematics and Computer Science
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Neural network segmentation of images from stained cucurbits leaves with colour symptoms of biotic and abiotic stresses
    Autorzy:
    Gocławski, J.
    Sekulska-Nalewajko, J.
    Kuźniak, E.
    Powiązania:
    https://bibliotekanauki.pl/articles/330961.pdf
    Data publikacji:
    2012
    Wydawca:
    Uniwersytet Zielonogórski. Oficyna Wydawnicza
    Tematy:
    segmentacja obrazu
    przestrzeń koloru
    przetwarzanie morfologiczne
    progowanie obrazu
    sztuczna sieć neuronowa
    ochrona roślin
    image segmentation
    colour space
    morphological processing
    image thresholding
    artificial neural network
    WTA learning
    Widrow-Hoff learning
    Cucurbita species
    plant stress
    ROS detection
    Opis:
    The increased production of Reactive Oxygen Species (ROS) in plant leaf tissues is a hallmark of a plant's reaction to various environmental stresses. This paper describes an automatic segmentation method for scanned images of cucurbits leaves stained to visualise ROS accumulation sites featured by specific colour hues and intensities. The leaves placed separately in the scanner view field on a colour background are extracted by thresholding in the RGB colour space, then cleaned from petioles to obtain a leaf blade mask. The second stage of the method consists in the classification of within mask pixels in a hue-saturation plane using two classes, determined by leaf regions with and without colour products of the ROS reaction. At this stage a two-layer, hybrid artificial neural network is applied with the first layer as a self-organising Kohonen type network and a linear perceptron output layer (counter propagation network type). The WTA-based, fast competitive learning of the first layer was improved to increase clustering reliability. Widrow-Hoff supervised training used at the output layer utilises manually labelled patterns prepared from training images. The generalisation ability of the network model has been verified by K-fold cross-validation. The method significantly accelerates the measurement of leaf regions containing the ROS reaction colour products and improves measurement accuracy.
    Źródło:
    International Journal of Applied Mathematics and Computer Science; 2012, 22, 3; 669-684
    1641-876X
    2083-8492
    Pojawia się w:
    International Journal of Applied Mathematics and Computer Science
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
      Wyświetlanie 1-5 z 5

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