Wyniki wyszukiwania - BazTech

1

The structure of classifiers of hand gestures with the use of the active contour model and Fourier descriptors

Golański P., Szczekala M.

Aviation Advances & Maintenance

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2018

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Vol. 41, Issue 1

63--77; 78--92

EN

In this article, the research results of the usage of selected methods of the analysis of images for the recognition of hand gestures in human-computer interaction was depicted. The usage of this type of interaction is important in case of the so-called wearable computers (computer is integrated with the work clothing of an operator. For the recognition of gestures, the combination of two methods associated with the image processing was suggested and that is the Chan-Vese active contour model enabling to recognize objects on a given image, based on the curve evolution technique, Mumford-Shah functional, level-sets and the methods to create shapes with the use of Fourier descriptors. For the classification criteria as a compatibility measure a scalable Mahalanobis distance was used.

PL

W artykule przedstawiono wyniki badań nad wykorzystaniem wybranych metod analizy obrazów do detekcji gestów dłoni w komunikacji człowiek–komputer. Wykorzystanie tego typu komunikacji ma duże znaczenie w przypadku obsługi komputerów zintegrowanych z odzieżą roboczą operatora, tzw. komputerów do noszenia (wearables computers). Do detekcji gestów zaproponowano połączenie dwóch metod związanych z obróbką obrazu: metodę aktywnych konturów Chana-Vese, umożliwiającą wykrywanie obiektów na danym obrazie, opartą na technikach ewolucji krzywych, funkcjonale Mumforda-Shaha oraz zbiorach poziomicowych, oraz metodę tworzenia klasyfikatorów kształtów z wykorzystaniem deskryptorów Fouriera. Do kryterium klasyfikacji jako miarę zgodności z wzorcem wykorzystano skalowaną odległość Mahalanobisa.

2

Automated object and image level classification of TB images using support vector neural network classifier

Priya E., Srinivasan S.

Biocybernetics and Biomedical Engineering

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2016

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Vol. 36, no. 4

670--678

EN

In this work, digital Tuberculosis (TB) images have been considered for object and image level classification using Multi Layer Perceptron (MLP) neural network activated by Support Vector Machine (SVM) learning algorithm. The sputum smear images are recorded under standard image acquisition protocol. The TB objects which include bacilli and outliers in the considered images are segmented using active contour method. The boundary of the segmented objects is described by fifteen Fourier Descriptors (FDs). The prominent FDs are selected using fuzzy entropy measures. These selected FDs of the TB objects are fed as input to the SVM learning algorithm of the MLP Neural Network (SVNN) and the result is compared with the state-of-the-art approach, Back Propagation Neural Network (BPNN). Results show that the segmentation method identifies the bacilli which retain their shape in-spite of artifacts present in the images. The methodology adopted has significantly enhanced the SVNN accuracy to 91.3% for object and 92.5% for image level classification than BPNN.

3

Separation of overlapping bacilli in microscopic digital TB images

Priya E., Srinivasan S.

Biocybernetics and Biomedical Engineering

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2015

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Vol. 35, no. 2

87--99

EN

The sputum smear microscopy based tuberculosis (TB) screening method is a conventional method employed for disease identification. It provides significant benefit to TB burdened communities across the globe; however, there are many challenges faced in processing the sputum smear images. When the smear is thick or uneven the number of overlapping bacilli is more which impedes the diagnosis. The separation of overlapping bacilli is significant without which the results lead to gross errors in identification of the disease causing agent. In this work, separation of overlapping bacilli is carried out by method of concavity (MOC) and is compared with the conventional methods such as multi-phase active contour (MAC) and marker-controlled watershed (MCW). Performance of the methods is evaluated based on the statistical mean quality score of shape descriptors extracted from the separated and existing true bacilli. The shape descriptors employed in this work include geometric features, Hu's, Zernike moments and Fourier descriptors. Results of separated overlapping bacilli demonstrate that MOC performs better than MAC and MCW. It is observed that the statistical mean quality score of the separated bacilli using the proposed MOC shows nearest match with true bacilli. The validation performed with experimental results to that of human annotations highlights the performance of MOC in separating the overlapping bacilli in the sputum smear images.

4

Assessment of pulverized coal combustion using Fourier descriptors

Kotyra A., Wójcik W., Golec T., Ławicki T.

Przegląd Elektrotechniczny

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2010

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R. 86, nr 7

241-243

EN

Article presents a mean to accessing combustion of pulverized coal with special attention to its stability. During several combustion tests, that have been done in laboratory facility, secondary, tertiary air flows have been changed as well as coal flow sp as to bring different combustion states. Flame boundary has been determined and expressed by Fourier descriptors. An influence of changing air/fuel ratio on Fourier descriptors has been examined.

PL

Artykuł podejmuje problem oceny procesu spalania pyłu węglowego ze zwróceniem szczególnej uwagi na jego stabilność. Przedstawiono stanowisko laboratoryjne na którym przeprowadzano testy spalania pyłu węglowego. W trakcie eksperymentu zmieniano istotne parametry wejściowe palnika jak przepływy powietrz wtórnych oraz wydatek węgla. W zarejestrowanych obrazach płomienia wyznaczono jego krawędź, następnie badano wpływ zmian parametrów wejściowych na jej reprezentację w postaci deskryptorów Fouriera.

5

Wykorzystanie deskryptorów Fouriera w diagnostyce procesu spalania

Kotyra A., Wójcik W.

Pomiary Automatyka Kontrola

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2008

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R. 54, nr 10

730-732

PL

W artykule przedstawiono wykorzystanie deskryptorów Fouriera opisujących kształt płomienia do określenia stabilności płomienia pyłowego. Badania wykonywane były na stanowisku laboratoryjnym, w czasie których zmieniano wydatki powietrza pierwotnego, wtórnego oraz pyłu węglowego doprowadzając do utraty stabilności płomienia.

EN

The paper presents the application of Fourier descriptors of the flame shape to assessment of the pulverised coal flame stability. Experiments were made on a laboratory stand equipped with a scaled down 1:10 swirl burner, while flows of the primary, secondary air as well as coal were changed. It caused lack of the flame stability, which could be observed through the changing flame shape. Flame images were captured by a monochrome CCD camera, mounted in an inspection opening, as shown in Fig. 1. Since the flame was the only luminous object, determination of its area and edge was based on a pixel amplitude. The flame edge was transformed into Fourier descriptors and was a subject of investigation.

6

Analiza rytmu serca z zastosowaniem metody NEFA

Kowalski H.

Prace Naukowe Politechniki Warszawskiej. Elektronika

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2007

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z. 161

17-22

EN

Acurate identification (classification) of ectopic beats is an important problem during ECG signal analysis. We developed a new Normalized Elliptic Fourier Descriptor Analysis (NEFA) method for three dimensional contour shape similitary analyses. We applied NEFA method to vectorcardiographic QRS loops shape analysis and then we performed the ECG rhythm analysis. We developed new version of spatial translation factor, time factor and NEFA shape size normalization stage. The study results confirm usefulness of NEFA method for automatic ECG signal analysis.