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EN
In the ceramic industry, quality control is performed using visual inspection in three different product stages: green, biscuit, and the final ceramic tile. To develop a real-time computer visual inspection system, the necessary step is successful tile segmentation from its background. In this paper, a new statistical multi-line signal change detection (MLSCD) segmentation method based on signal change detection (SCD) method is presented. Through experimental results on seven different ceramic tile image sets, MLSCD performance is analyzed and compared with the SCD method. Finally, recommended parameters are proposed for optimal performance of the MLSCD method.
EN
The strong earthquake with magnitude 6.9 occurred ofshore at the northernmost edge of the Samos Island and was strongly felt in the north Aegean islands and İzmir metropolitan city. In this study, the effective elastic thicknesses of the lithosphere and seismogenic layer thickness were correlated with each other in order to understand the nature of the earthquakes. We determined that the upper and lower depth limits of seismogenic layer are in a range of 5–15 km, meaning that only the upper crust is mostly involved in earthquakes in the study area. The fact that seismogenic layer and effective elastic thicknesses are close to each other indicates that the earthquake potential may be within the seismogenic layer. Following that, we estimate the stress feld from the geoid undulations as a proxy of gravity potential energy in order to analyze the amplitude and orientation of the stress vectors and seismogenic behavior implications. The discrete wavelet transform has been carried out to decompose the isostatic residual gravity anomalies into horizontal, vertical and diagonal detail coefcients. The results delineated edges of gravity anomalies that reveal some previously unknown features.
EN
Real-time traffic monitoring and parking are very important aspects for a better social and economic system. Python-based Intelligent Parking Management System (IPMS) module using a USB camera and a canny edge detection method was developed. The current situation of real-time parking slot was simultaneously checked, both online and via a mobile application, with a message of Parking “Available” or “Not available” for 10 parking slots. In addition, at the time entering in parking module, gate open and at the time of exit parking module, the gate closes automatically using servomotor and sensors. Results are displayed in figures with the proposed method flow chart.
EN
Continuous improvement of semiconductor chip technology allows more and more complex functions to be performed by an increasing number of modules with limited space and power. The deep miniaturisation and cost reduction of such modules has a positive impact on their application areas. They can be used, for example, inside machine tools for dimensional inspection of workpieces or deformation of the tool tip. Modules of this type must contain as many standard components as possible and, in particular, a processing unit responsible, among other things, for processing the optical sensor signal. For this reason, this study reviews and compares algorithms for object edge detection useful in embedded systems based on standard single chips, cores based on Cortex-M4F. The complexity of processing and the quality of algorithm output data was analysed. The results of experimental studies are presented. It was found that the required processing times significantly reduce the use of single chip embedded systems only for edge detection on small images.
5
Content available Detecting visual objects by edge crawling
EN
Content-based image retrieval methods develop rapidly with a growing scale of image repositories. They are usually based on comparing and indexing some image features. We developed a new algorithm for finding objects in images by traversing their edges. Moreover, we describe the objects by histograms of local features and angles. We use such a description to retrieve similar images fast. We performed extensive experiments on three established image datasets proving the effectiveness of the proposed method.
EN
Nowadays, unprecedented amounts of heterogeneous data collections are stored, processed and transmitted via the Internet. In data analysis one of the most important problems is to verify whether data observed or/and collected in time are genuine and stationary, i.e. the information sources did not change their characteristics. There is a variety of data types: texts, images, audio or video files or streams, metadata descriptions, thereby ordinary numbers. All of them changes in many ways. If the change happens the next question is what is the essence of this change and when and where the change has occurred. The main focus of this paper is detection of change and classification of its type. Many algorithms have been proposed to detect abnormalities and deviations in the data. In this paper we propose a new approach for abrupt changes detection based on the Parzen kernel estimation of the partial derivatives of the multivariate regression functions in presence of probabilistic noise. The proposed change detection algorithm is applied to oneand two-dimensional patterns to detect the abrupt changes.
EN
This article presents examples of the use of image filtering for various types of diagnostic medical imaging in order to improve their interpretative value, and thus to improve the diagnostic reliability of that imaging. As research and visual tests have shown, in many cases, the use of digital image filtering makes it possible to significantly improve not only image quality, but also their readability or clarity, thus contributing to a more accurate and precise reading and interpretation of information contained in the images. The author proposed specific filters that largely meet the assumed conditions and constitute a supplement, and sometimes introduce a possible new application in addition to those already known in subject literature. A visual assessment was also made of the degree of diagnostic usefulness of images after filtration compared to the source images. The most commonly used filters are those that not only help to improve the overall appearance and quality of the image, but also, on the one hand, help to extract or highlight certain information, or to reduce noise, on the other hand. Thanks to these solutions, it is possible to smoothen or sharpen some structures within the images, which impacts their readability and quality. Thus, image filtering has become a very desirable and useful tool in many fields of science, technology, as well as art and medicine. The subject matter of image transformation is here applied to the latter discipline.
PL
W niniejszym artykule przedstawiono przykłady zastosowania filtracji dla różnych rodzajów medycznej diagnostyki obrazowej, celem polepszenia ich wartości interpretacyjnej, a tym samym – podniesienia wiarygodności diagnostycznej obrazu. Jak wykazały badania i testy wizualne - w wielu przypadkach, stosowanie filtracji obrazów cyfrowych umożliwia znaczne poprawienie nie tylko ich jakości, a co za tym idzie czytelności czy klarowności, przyczyniając się do bardziej trafnego i precyzyjnego odczytywania i interpretowania informacji znajdujących się na obrazach. Autor zaproponował określone filtry, które w znacznym stopniu spełniają założone warunki i stanowią uzupełnienie, a niekiedy są nową propozycją w stosunku do znanych z literatury. Dokonano również wizualnej oceny stopnia przydatności diagnostycznej obrazów po filtracji w porównaniu z obrazami źródłowymi. Najczęściej używanymi filtrami są te, które nie tylko pomagają poprawić ogólny wygląd i jakość zdjęcia, ale wyodrębniają bądź uwypuklają pewne informacje – z jednej strony lub redukują szumy – z drugiej. Dzięki nim można dokonać wygładzenia bądź wyostrzenia niektórych struktur na obrazie, co wpływa na ich czytelność i jakość . Tak więc filtracja stała się narzędziem bardzo pożądanym i przydatnym w wielu dziedzinach nauki, techniki , również sztuki i medycyny, której to dziedziny dotyczy przedstawiona tematyka transformacji obrazu.
EN
Noise reduction of images is a challenging task in image processing. Salt and pepper noise is one kind of noise that affects a gray-scale image significantly.Generally, the median filter is used to reduce salt and pepper noise; it gives optimum results while compared to other image filters. Median filter works only up to a certain level of noise intensity. Here we proposed a neighborhoodbased image filter called nbd-filter, it works perfectly for gray image regardless of noise intensity. It reduces salt and pepper noise significantly at any noise level and produces a noise-free image. Further, we proposed an edge detection algorithm based on the neutrosophic set, it detects edges efficiently for images corrupted by noise and noise-free images. Neutrosophic set (NS) is a powerful tool to deal with indeterminacy. Since most of the real-life images consists of indeterminate regions, Neutrosophy is a perfect tool for edge detection. In this paper, the neutrosophic set is applied to the image domain and a novel edge detection technique is proposed.
PL
Celem pracy jest zaproponowanie metody wykrywania krawędzi o ściśle określonym kierunku przebiegu na danych obrazowych i laserowych. Tradycyjne filtry wykrywają krawędzie we wszystkich kierunkach (np. filtr Canny), ewentualnie w trzech wybranych – horyzontalnym, wertykalnym lub diagonalnym (np. filtr Roberts). Często przedmiotem analiz są tylko określone obiekty liniowe jak linie energetyczne, tory, czy rurociągi. Mają one zazwyczaj ściśle określone kierunki przebiegu. Klasyczne filtry wykrywają oczywiście te informacje, ale także dużą ilość danych nadmiarowych, które utrudniają dalsze analizy. Problemem postawionym w pracy jest znalezienie takiego rozwiązania, które pozwoliłoby na wyznaczenie krawędzi tylko i wyłącznie o ściśle określonym kierunku, odpowiadających za przebieg konkretnych obiektów takich jak tory kolejowe, rurociągi czy linie energetyczne. Problem badawczy skupiał się w pierwszym etapie na określeniu przybliżonej lokalizacji wyłącznie analizowanych obiektów, a w kolejnym kroku na poprawnej i dokładnej ich detekcji. Pierwszy etap został przeprowadzony z wykorzystaniem filtrów Gabora, drugi - z użyciem transformaty Hougha. Testy zostały wykonane zarówno dla danych laserowych jak i danych obrazowych w postaci ortofotomapy. W obydwu przypadkach uzyskano dobre rezultaty dla obydwóch etapów: przybliżonej lokalizacji i precyzyjnej detekcji.
EN
This article presents a method for detecting linear objects with a defined direction based on image and lidar data. It was decided to use Gabor waves for this purpose. The Gabor wavelet is a sinusoid modulated by the Gauss function. The orientation angle of the sinusoid means that the waveform can only operate in strictly defined directions. It should, therefore, provide an appropriate solution to the problem posed by the publication. The research problem focused in the first stage on determining the approximate location of only the analysed objects, and in the next step on correct and accurate detection. The first stage was carried out using Gabor filters, the second - using the Hough transform. The tests were performed for both laser data and image data. In both cases, good results were obtained for both stages: approximate location and precise detection.
EN
The continuous shift of shoreline boundaries due to natural or anthropogenic events has created the necessity to monitor the shoreline boundaries regularly. This study investigates the perspective of implementing artifcial intelligence techniques to model and predict the realignment in shoreline along the eastern Indian coast of Orissa (now called Odisha). The modeling consists of analyzing the satellite images and corresponding reanalysis data of the coastline. The satellite images (Landsat imagery) of the Orissa coastline were analyzed using edge detection flters, mainly Sobel and Canny. Sobel and canny flters use edge detection techniques to extract essential information from satellite images. Edge detection reduces the volume of data and flters out worthless information while securing signifcant structural features of satellite images. The image diferencing technique is used to determine the shoreline shift from GIS images (Landsat imagery). The shoreline shift dataset obtained from the GIS image is used together with the metrological dataset extracted from Modern-Era Retrospective analysis for Research and Applications, Version 2, and tide and wave parameter obtained from the European Centre for Medium-Range Weather Forecast for the period 1985–2015, as input parameter in machine learning (ML) algorithms to predict the shoreline shift. Artifcial neural network (ANN), k-nearest neighbors (KNN), and support vector machine (SVM) algorithm are used as a ML model in the present study. The ML model contains weights that are multiplied with relevant inputs/features to obtain a better prediction. The analysis shows wind speed and wave height are the most prominent features in shoreline shift prediction. The model’s performance was compared, and the observed result suggests that the ANN model outperforms the KNN and SVM model with an accuracy of 86.2%.
11
Content available remote Creating see-around scenes using panorama stitching
EN
Image stitching refers to the process of combining multiple images of the same scene to produce a single high-resolution image, known as panorama stitching. The aim of this paper is to produce a high-quality stitched panorama image with less computation time. This is achieved by proposing four combinations of algorithms. First combination includes FAST corner detector, Brute Force K-Nearest Neighbor (KNN) and Random Sample Consensus (RANSAC). Second combination includes FAST, Brute Force (KNN) and Progressive Sample Consensus (PROSAC). Third combination includes ORB, Brute Force (KNN) and RANSAC. Fourth combination contains ORB, Brute Force (KNN) and PROSAC. Next, each combination involves a calculation of Transformation Matrix. The results demonstrated that the fourth combination produced a panoramic image with the highest performance and better quality compared to other combinations. The processing time is reduced by 67% for the third combination and by 68% for the fourth combination compared to stat-of-the-art.
PL
W artykule przedstawiono projekt architektury oraz implementację układową toru przetwarzania wstępnego obrazu z modułem detekcji krawędzi. Układ został zaimplementowany w FPGA Intel Cyclone. Zrealizowany moduł wykorzystuje pięć wybranych algorytmów wykrywania krawędzi, w tym Robertsa, Sobela i Prewitt.
EN
The paper presents FPGA implementation details of the hardware image processing block with the edge detection module. In the implemented video processing module we use five selected edge detection algorithms, including Roberts, Sobel and Prewitt. The structure was synthesized and packed using hardware design platform built around the Intel Cyclone V FPGA. The number of logic elements used in each implementation was compared. We also estimated the execution time and maximum possible frame rate in VGA (640x480) and FullHD (1920x1080) video stream.
EN
Active contour model is a typical and effective closed edge detection algorithm, which has been widely applied in remote sensing image processing. Since the variety of the image data source, the complexity of the application background and the limitations of edge detection, the robustness and universality of active contour model are greatly reduced in the practical application of edge extraction. This study presented a fast edge detection approach based on global optimization convex model and Split Bregman algorithm. Firstly, the proposed approach defined a generalized convex function variational model which incorporated the RSF model’s principle and Chan’s global optimization idea and could get the global optimal solution. Secondly, a fast numerical minimization scheme based on split Bregman iterative algorithm is employed for overcoming drawbacks of noise and others. Finally, the curve evolves to the target boundaries quickly and accurately. The approach was applied in real special sea ice SAR images and synthetic images with noise, fuzzy boundaries and intensity inhomogeneity, and the experiment results showed that the proposed approach had a better performance than the edge detection methods based on the GMAC model and RSF model. The validity and robustness of the proposed approach were also verified.
PL
Artykuł opisuje system do monitoringu pomieszczeń zamkniętych oparty na zespole kamer internetowych. System umożliwia rejestrację obrazu za pomocą trzech kamer internetowych w momencie wykrycia ruchu i przekazuje w czasie rzeczywistym nagrany film użytkownikowi na dowolne urządzenie posiadające system Android. Dzięki takiemu rozwiązaniu można kontrolować dane pomieszczenie np. pokój dziecka, biuro czy też sklep. Umożliwia to podjęcie szybszej reakcji w z związku detekcją poruszającego się obiektu. System, po wykryciu ruchu w pomieszczeniu, rejestruje przez określony czas sekwencje obrazów. Poza opracowaniem odpowiedniego kodu analizującego obraz z kamery internetowej składa się z odpowiedniej infrastruktury sprzętowej oraz aplikacji przeznaczonej dla systemu Android.
EN
The article presents a monitoring system based on a set of webcams. The system allows to record the movie from three webcams at the moment of motion detection in real-time. User have an access to the movies by application on Android device. Three most popular edges detection algorithms were implemented and tested: Laplace’s processing, Sobel mask and Canny algorithm. Authors elaborated the three edge detection algorithms and tested their functionality in presence and absence of moving object in different natural lighting conditions – day and night. For each situation (day/night, presence/absence of movement) one thousand single tests were carried out. The detection was conducted every 66 ms. The tests prove that the Laplace's operator is the most effective edge algorithm for this task. A program based on the Laplce operator does not perform erroneous motion detection and its efficiency in the presence of a moving object is over 96%. The Canny algorithm would only apply in the day if it were to be used in the RGB. Worst of all, Sobel's operator, has so high sensitivity that it detects the movement almost all the time event if it not occurs.
15
Content available remote Metody wizyjne w automatyzacji spawania
PL
W artykule omówiono problematykę wdrożenia systemu wizyjnego do sterowania procesem spawalniczym. Zaprezentowano podstawowe sposoby usuwania zakłóceń oraz algorytmy rozpoznawania obrazu. Przetestowano dostępne na rynku czujniki.
EN
The article discusses the issues of implementation of the vision system to control the welding process. The basic methods of removing noises and image recognition algorithms were presented. Commercially available sensors were tested.
EN
The paper presents the circular Hough transform in the process of detecting and counting coins. The issues of linear and circular Hough transform are discussed. An algorithm for counting coins in a three-dimensional image using the discrete Hough space is demonstrated. Moreover, the results of the application for detecting and counting coins in a static image and video stream are presented. Observations of histograms for HSV and RGB color palettes, for different camera resolutions and various parameters of image segmentation, edge detection and smoothing filter have been made.
EN
This paper demonstrates the application of different image processing techniques to process high resolution visual images and merge it with low resolution thermograms to improve its level of detail. The same idea is applied in commercially available thermal cameras (e.g. FLIR with MSX® technology). Low resolution thermograms considered in this paper were obtained from a thermal scanner with point infrared detector (Fig. 1) sensitive to long wavelength infrared spectral range. The proposed algorithms are Laplacian, Sobel operator, embossing and Gaussian differential blur (described in section 3). The authors processed 6 different thermograms to qualitatively assess obtained results. It was done in a statistical manner through a survey and revealed that both Sobel operator and embossing provided the most clear, detailed and unambiguous results (Fig. 5). Such algorithms may be applied for processing more channels in a multispectral, cost-effective system.
EN
In this paper we present a novel approach for image description. The method is based on two well-known algorithms: edge detection and blob extraction. In the edge detection step we use the Canny detector. Our method provides a mathematical description of each object in the input image. On the output of the presented algorithm we obtain a histogram, which can be used in various fields of computer vision. In this paper we applied it in the content-based image retrieval system. The simulations proved the effectiveness of our method.
PL
W pracy przedstawiono możliwości zastosowania jednostki GPU do wyznaczenia krawędzi dla obrazów spalania pyłu węglowego. Porównano czas wykonywania operacji oraz dokładność detekcji brzegu obszaru płomienia. Wykorzystano metodę opartą o model konturu aktywnego Chan-Vese. Wyniki badań pokazują, że nastąpiło znaczne przyśpieszenie wykonywania operacji (ok. 400%).
UK
У статті представлені можливості використання пристрою GPU для визначення країв зображення при спалюванні вугільного пилу. Порівняно час виконання і точність виявлення краю області полум'я. Використовується метод, заснований на моделі активного контуру Chan-Vese. Результати досліджень показують, що відбулося істотне прискорення операцій (прибл. 400%).
EN
This paper presents possibility of using GPU to determine the edge of the image pulverized combustion coal. Compared are the operation time and the accuracy of edge detection area of the flame. Used a method based on the active contour model Chan-Vese. The results show that there was a significant acceleration of the operation (up to 400%).
PL
Wykrywanie przejść dla pieszych wykonywane w aplikacji działającej na telefonie komórkowym jest jednym z elementów ułatwiających poruszanie się po mieście osób niewidomych i słabo widzących. W pracy przedstawiono algorytm wykrywania przejść dla pieszych na zdjęciach wykonanych telefonem komórkowym. Ważnym jego elementem jest filtracja punktów należących do krawędzi pasów przejścia i dwuetapowa agregacja tych punktów w krawędzie przejścia. Przedstawiono wyniki dla rzeczywistych zdjęć pasów dla pieszych wykonanych aparatem telefonu komórkowego w trudnych, zimowych warunkach.
EN
Zebra-crossings detection in a mobile application is one of mobility aids for the blind and partially-sighted. This paper presents an algorithm for the detection of pedestrian crossings in images taken with mobile phone. Its important element is the filtering of points belonging to the edge of zebra-crossing stripes and two-step aggregation of these points into the stripes edges. The results for the real zebracrossing images taken with the mobile phone camera in tough winter conditions are presented.
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