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Wyświetlanie 1-15 z 23
Tytuł:
Image Retrieval Based on Text and Visual Content Using Neural Networks
Autorzy:
Castro, D. A.
Seijas, L. M.
Powiązania:
https://bibliotekanauki.pl/articles/108732.pdf
Data publikacji:
2010
Wydawca:
Społeczna Akademia Nauk w Łodzi
Tematy:
image retrieval
Self-Organizing Maps (SOM)
content-based image retrieval (CBIR)
Text-Based Image Retrieval (TBIR)
ParBSOM
Scoring function
Opis:
In the last few years there has been a dramatic increase in the amount of visual data to be searched and retrieved. Typically, images are described by their textual content (TBIR) or by their visual features (CBIR). However, these approaches still present many problems. The hybrid approach was recently introduced, combining both characteristics to improve the benefits of using text and visual content separately. In this work we examine the use of the Self Organizing Maps for content-based image indexing and retrieval. We propose a scoring function which eliminates irrelevant images from the results and we also introduce a SOM variant (ParBSOM) that reduces training and retrieval times. The application of these techniques to the hybrid approach improved computational results.
Źródło:
Journal of Applied Computer Science Methods; 2010, 2 No. 1; 21-39
1689-9636
Pojawia się w:
Journal of Applied Computer Science Methods
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Optimized image feature selection using pairwise classifiers
Autorzy:
Bazarganigilani, M.
Powiązania:
https://bibliotekanauki.pl/articles/91755.pdf
Data publikacji:
2011
Wydawca:
Społeczna Akademia Nauk w Łodzi. Polskie Towarzystwo Sieci Neuronowych
Tematy:
content based image retrieval systems
content-based image retrieval (CBIR)
higher feature
classifier
Opis:
In this paper, we introduce an optimized method to improve the accuracy of content based image retrieval systems (CBIR). CBIR systems classify the images according to low and higher features.In our research, we improve both feature selection and classifier partition of a CBIR system. Results show great performance of our proposed algorithm.
Źródło:
Journal of Artificial Intelligence and Soft Computing Research; 2011, 1, 2; 147-153
2083-2567
2449-6499
Pojawia się w:
Journal of Artificial Intelligence and Soft Computing Research
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Similarity analysis in medical image databases
Autorzy:
Rumiński, J.
Powiązania:
https://bibliotekanauki.pl/articles/1954510.pdf
Data publikacji:
1999
Wydawca:
Politechnika Gdańska
Tematy:
image retrieval
image analysis
descriptors
query algebra
Opis:
The review of methods of similarity analysis of medical images is presented. Feature extraction, feature representation and different concepts of image query algebra problems are described and discussed from the medical application point of view. New algorithms based on medical image regularity description and intensity description are proposed. As a conclusion a Java application "ObrazMed" for content based medical image analysis is presented.
Źródło:
TASK Quarterly. Scientific Bulletin of Academic Computer Centre in Gdansk; 1999, 3, 4; 419-444
1428-6394
Pojawia się w:
TASK Quarterly. Scientific Bulletin of Academic Computer Centre in Gdansk
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Fast image index for database management engines
Autorzy:
Grycuk, Rafał
Najgebauer, Patryk
Kordos, Miroslaw
Scherer, Magdalena M.
Marchlewska, Alina
Powiązania:
https://bibliotekanauki.pl/articles/1837480.pdf
Data publikacji:
2020
Wydawca:
Społeczna Akademia Nauk w Łodzi. Polskie Towarzystwo Sieci Neuronowych
Tematy:
image descriptor
content-based image retrieval
image indexing
Opis:
Large-scale image repositories are challenging to perform queries based on the content of the images. The paper proposes a novel, nested-dictionary data structure for indexing image local features. The method transforms image local feature vectors into two-level hashes and builds an index of the content of the images in the database. The algorithm can be used in database management systems. We implemented it with an example image descriptor and deployed in a relational database. We performed the experiments on two image large benchmark datasets.
Źródło:
Journal of Artificial Intelligence and Soft Computing Research; 2020, 10, 2; 113-123
2083-2567
2449-6499
Pojawia się w:
Journal of Artificial Intelligence and Soft Computing Research
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Semantic hashing for fast solar magnetogram retrieval
Autorzy:
Grycuk, Rafał
Scherer, Rafał
Marchlewska, Alina
Napoli, Christian
Powiązania:
https://bibliotekanauki.pl/articles/2147145.pdf
Data publikacji:
2022
Wydawca:
Społeczna Akademia Nauk w Łodzi. Polskie Towarzystwo Sieci Neuronowych
Tematy:
content-based image retrieval
image descriptor
solar analysis
Opis:
We propose a method for content-based retrieving solar magnetograms. We use the SDO Helioseismic and Magnetic Imager output collected with SunPy PyTorch libraries. We create a mathematical representation of the magnetic field regions of the Sun in the form of a vector. Thanks to this solution we can compare short vectors instead of comparing full-disk images. In order to decrease the retrieval time, we used a fully-connected autoencoder, which reduced the 256-element descriptor to a 32-element semantic hash. The performed experiments and comparisons proved the efficiency of the proposed approach. Our approach has the highest precision value in comparison with other state-of-the-art methods. The presented method can be used not only for solar image retrieval but also for classification tasks.
Źródło:
Journal of Artificial Intelligence and Soft Computing Research; 2022, 12, 4; 299--306
2083-2567
2449-6499
Pojawia się w:
Journal of Artificial Intelligence and Soft Computing Research
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
MUSEUM AS A VISUAL LAB? CULTURE-TECHNOLOGY NETWORKS IN CBIR PROJECTS
Autorzy:
Olszewska, Anna
Gancarczyk, Joanna
Powiązania:
https://bibliotekanauki.pl/articles/646737.pdf
Data publikacji:
2017
Wydawca:
Akademia Górniczo-Hutnicza im. Stanisława Staszica w Krakowie
Tematy:
visual culture, image recognition, digital image retrieval, museum, library
Opis:
Should any museum or scientific library consider itself as an information technology laboratory?This article explores the lives of several pioneering museum and library projects focused on digital image retrieval techniques (CBIR). The research aims to contribute critical evaluation of museum and information technology domain relations in the field. The outcomes may be applied in the planning of future co-operative endeavours. The analysis begins with a discussion of projects in which a museum or library played the role of data pro- vider for image analysis development and testing (i.e. SWIC, Collage, SHREW systems). This is followed by a study of schemes focused on technology and implementing a standard image search methodology used for access to museum collections (i.e. QBIC, Artiste). The final part of the paper deals with the projects animated by museums or libraries themselves (BSB, Oxford Ballads Online, PrintArt) and the example of a consort that focuses on the specific type of visual resources (the Bernstein project).
Źródło:
Studia Humanistyczne AGH; 2017, 16, 2
2084-3364
Pojawia się w:
Studia Humanistyczne AGH
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
An autonomous monitoring system based on object shape detection
Autorzy:
Deniziak, S.
Michno, T.
Pięta, P.
Powiązania:
https://bibliotekanauki.pl/articles/114662.pdf
Data publikacji:
2015
Wydawca:
Stowarzyszenie Inżynierów i Techników Mechaników Polskich
Tematy:
monitoring system
object identification
image retrieval
machine vision
Opis:
In traditional monitoring systems, stationary cameras are supervised only by a human operator, who may easily miss some events recorded by a camera. Because it is imperative for a surveillance system to be reliable, its autonomy can be extended by applying computer vision algorithms to a video signal and also by the use of mobile robots capable of monitoring tight and occluded areas. In this paper, we present an overview of the concept of an autonomous monitoring system based on object shape detection. Our goal is to develop a real-time system which robustly and efficiently identifies objects on the basis of their approximate shape. For monitoring the environment we use active and smart cameras capable of remote position control, as well as mobots equipped with video sensors. After performing the object extraction from individual video frames, each new detected object is decomposed into simple graphical primitives like lines, circles, rectangles etc. and then identified in a database using the Query by Shape (QS) method.
Źródło:
Measurement Automation Monitoring; 2015, 61, 7; 349-351
2450-2855
Pojawia się w:
Measurement Automation Monitoring
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Detecting visual objects by edge crawling
Autorzy:
Grycuk, Rafał
Wojciechowski, Adam
Wei, Wei
Siwocha, Agnieszka
Powiązania:
https://bibliotekanauki.pl/articles/1837538.pdf
Data publikacji:
2020
Wydawca:
Społeczna Akademia Nauk w Łodzi. Polskie Towarzystwo Sieci Neuronowych
Tematy:
content-based image retrieval
crawler
edge detection
image descriptor
object extraction
Opis:
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.
Źródło:
Journal of Artificial Intelligence and Soft Computing Research; 2020, 10, 3; 223-237
2083-2567
2449-6499
Pojawia się w:
Journal of Artificial Intelligence and Soft Computing Research
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Efficient image retrieval by fuzzy rules from boosting and metaheuristic
Autorzy:
Korytkowski, Marcin
Senkerik, Roman
Scherer, Magdalena M.
Angryk, Rafal A.
Kordos, Miroslaw
Siwocha, Agnieszka
Powiązania:
https://bibliotekanauki.pl/articles/91856.pdf
Data publikacji:
2020
Wydawca:
Społeczna Akademia Nauk w Łodzi. Polskie Towarzystwo Sieci Neuronowych
Tematy:
image retrieval
fuzzy rules
local image features
pobieranie obrazu
lokalne funkcje obrazu
Opis:
Fast content-based image retrieval is still a challenge for computer systems. We present a novel method aimed at classifying images by fuzzy rules and local image features. The fuzzy rule base is generated in the first stage by a boosting procedure. Boosting meta-learning is used to find the most representative local features. We briefly explore the utilization of metaheuristic algorithms for the various tasks of fuzzy systems optimization. We also provide a comprehensive description of the current best-performing DISH algorithm, which represents a powerful version of the differential evolution algorithm with effective embedded mechanisms for stronger exploration and preservation of the population diversity, designed for higher dimensional and complex optimization tasks. The algorithm is used to fine-tune the fuzzy rule base. The fuzzy rules can also be used to create a database index to retrieve images similar to the query image fast. The proposed approach is tested on a state-of-the-art image dataset and compared with the bag-of-features image representation model combined with the Support Vector Machine classification. The novel method gives a better classification accuracy, and the time of the training and testing process is significantly shorter.
Źródło:
Journal of Artificial Intelligence and Soft Computing Research; 2020, 10, 1; 57-69
2083-2567
2449-6499
Pojawia się w:
Journal of Artificial Intelligence and Soft Computing Research
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Optimizing Space Complexity using Color Spaces in CBIR Systems for Medical Diagnosis
Autorzy:
Kenny, S. Pradeep Kumar
Powiązania:
https://bibliotekanauki.pl/articles/1031845.pdf
Data publikacji:
2020
Wydawca:
Przedsiębiorstwo Wydawnictw Naukowych Darwin / Scientific Publishing House DARWIN
Tematy:
Cervical Cancer
Color Space
Content Based Image retrieval
Data Mining
Opis:
Content based Image Retrieval systems are now used in various automated systems because they largely produce accurate results as they do not depend on the metadata for telling what the image is but rather define it on the basis contents of the image like color, shape, texture and spatial locations. Content based Image retrieval systems have a repository of similar images and when a query image is presented to system it matches similar images in the database. This process aids in various applications like security checks to medical diagnosis. But all CBIR systems in common have to store the images which take a huge space. Here in this work, a unique approach is being devised to reduce the space complexity for a CBIR system used for detecting cervical cancer. When it comes to medical image it is not the question of how to reduce space, but along with it, the original contents of the image also has to be preserved.
Źródło:
World News of Natural Sciences; 2020, 30, 2; 96-103
2543-5426
Pojawia się w:
World News of Natural Sciences
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Techniki semantycznego indeksowania obrazów medycznych na przykładzie przestrzennych rekonstrukcji unaczynienia wieńcowego
Semantic techniques of image retrieval on the example of CT coronary vessels reconstructions
Autorzy:
Trzupek, M.
Ogiela, M. R.
Powiązania:
https://bibliotekanauki.pl/articles/153096.pdf
Data publikacji:
2013
Wydawca:
Stowarzyszenie Inżynierów i Techników Mechaników Polskich
Tematy:
semantyczne indeksowanie i wyszukiwanie obrazów medycznych
systemy CBIR
systemy automatycznej analizy i rozumienia obrazów
semantic image retrieval
content-based image retrieval (CBIR)
image understanding systems
intelligent medical image processing and understanding
Opis:
W artykule zaprezentowano techniki semantycznego indeksowania danych obrazowych w medycznych bazach danych z wykorzystaniem grafowych formalizmów lingwistyki matematycznej. Zaproponowane rozwiązania w głównej mierze predestynowane są do wizualizacji pochodzących z obrazowania CT (przestrzennych rekonstrukcji unaczynienia wieńcowego), niemniej jednak przedstawiona metodologia może również stanowić bazę dla innej klasy obrazów medycznych.
The wide spread of multimedia medical databases has shown that the problem of storing and effectively searching for images containing specific disease cases that are significant for medical diagnostics is still fraught with great difficulties. The paper presents semantic indexing techniques in medical imaging databases using graph-based mathematical linguistic formalisms. The proposed solutions are mainly predestined for visualizations obtained from diagnostic examinations with the use of computed tomography (spatial reconstructions of the coronary vascularisation), but the presented methodology can also be a basis for a different class of medical images. The first section describes the methods and limitations in the context of storing and searching for data in medical databases of contemporary systems. The second section presents the historical background and discusses examples of systems. The third section describes next steps of the proposed methodology, which is additionally shown in Fig. 3. The last section summarizes the proposed solutions in the context of other systems and indicates further research directions. The obtained results confirm the possibility of using the proposed solutions in the specialized medical databases.
Źródło:
Pomiary Automatyka Kontrola; 2013, R. 59, nr 1, 1; 43-46
0032-4140
Pojawia się w:
Pomiary Automatyka Kontrola
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Content-based image retrieval using a signature graph and a self-organizing map
Autorzy:
Van, T. T.
Le, T. M.
Powiązania:
https://bibliotekanauki.pl/articles/330159.pdf
Data publikacji:
2016
Wydawca:
Uniwersytet Zielonogórski. Oficyna Wydawnicza
Tematy:
binary signature
similarity measure
signature graph
image retrieval
sygnatura binarna
miara podobieństwa
wyszukiwanie obrazu
Opis:
In order to effectively retrieve a large database of images, a method of creating an image retrieval system CBIR (content-based image retrieval) is applied based on a binary index which aims to describe features of an image object of interest. This index is called the binary signature and builds input data for the problem of matching similar images. To extract the object of interest, we propose an image segmentation method on the basis of low-level visual features including the color and texture of the image. These features are extracted at each block of the image by the discrete wavelet frame transform and the appropriate color space. On the basis of a segmented image, we create a binary signature to describe the location, color and shape of the objects of interest. In order to match similar images, we provide a similarity measure between the images based on binary signatures. Then, we present a CBIR model which combines a signature graph and a self-organizing map to cluster and store similar images. To illustrate the proposed method, experiments on image databases are reported, including COREL, Wang and MSRDI.
Źródło:
International Journal of Applied Mathematics and Computer Science; 2016, 26, 2; 423-438
1641-876X
2083-8492
Pojawia się w:
International Journal of Applied Mathematics and Computer Science
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Dopasowywanie obrazów sonarowych w oparciu o metodę informacji wzajemnej
matching sonar images based on the mutual information method
Autorzy:
Chorzewska, K.
Felski, A.
Powiązania:
https://bibliotekanauki.pl/articles/222148.pdf
Data publikacji:
2012
Wydawca:
Akademia Marynarki Wojennej. Wydział Dowodzenia i Operacji Morskich
Tematy:
sonogram
cyfrowa analiza obrazu
wyszukiwanie na podstawie zawartości
dopasowywanie obrazów
digital image analysis
content-based image retrieval (CBIR)
image matching
Opis:
Wśród wielu zagrożeń dla współczesnej żeglugi morskiej wymienia się między innymi zagrożenie terroryzmem. Na wodach płytkich może ono przyjmować postać zagrożenia improwizowanymi ładunkami wybuchowymi umieszczanymi na dnie z pokładów dowolnych jednostek, pojawiających się na akwenie w sposób niezauważalny dla kogokolwiek. Jednym z kierunków działań zmierzających do poprawy bezpieczeństwa w tym zakresie jest koncepcja hydroakustycznego systemu ochrony portów, torów wodnych i kotwicowisk. Zakłada ona możliwość szybkiego porównywania obrazów sonarowych z obrazami archiwalnymi, dając podstawy do wykrywania zmian na ochranianym akwenie, przy czym powszechna dostępność technik cyfrowych sugeruje wykonywanie takich poszukiwań w tej właśnie technologii. Porównywanie sonogramów metodami cyfrowej analizy obrazów wymaga w pierwszej kolejności przeprowadzenia ich prawidłowego automatycznego dopasowania. Automatyzacja procesu dopasowania obrazów otwiera dodatkowo perspektywy ich zastosowania w systemach nawigacji porównawczej. W artykule przedstawiono ujęcie tego zagadnienia w sposób właściwy dla technik wyszukiwania obrazów na podstawie zawartości (Content-Based Image Retrieval — CBIR). Wyznaczenie najlepszego dopasowania dwóch sonogramów przeprowadzono w oparciu o metodę maksymalizacji informacji wzajemnej.
Among many threats to the present maritime navigation the terrorism has risen to the rank of one of the most serious. In shallow waters there is a possibility of using the improvised explosive devices which can be placed on the seabed impromptu and imperceptible for anybody from deck of any watercraft or from a harbor quay. One of the proposals to improve the safety in this area is the idea of hydro acoustic surveillance system of ports, fairways and anchorages. It is based on the assumption that sonar images can be quickly compared with archived images leading to detecting changes in the waters protected. Widespread access to digital technologies suggests using them to deal with the problem mentioned. However, to compare sonograms with the digital picture analysis methods requires, first of all, their proper automatic adjustment. The automation of the image-matching process also opens perspectives for using it in systems based on the comparative navigation. The paper presents the approach to the issue based on Content-Based Image Retrieval (CBIR).The Mutual Information method is employed to best match two sonograms.
Źródło:
Zeszyty Naukowe Akademii Marynarki Wojennej; 2012, R. 53 nr 4 (191), 4 (191); 19-32
0860-889X
Pojawia się w:
Zeszyty Naukowe Akademii Marynarki Wojennej
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Image retrieval based on hierarchical Gabor filters
Autorzy:
Andrysiak, T.
Choraś, M.
Powiązania:
https://bibliotekanauki.pl/articles/908448.pdf
Data publikacji:
2005
Wydawca:
Uniwersytet Zielonogórski. Oficyna Wydawnicza
Tematy:
filtr Gabora
pobieranie obrazu
ekstrakcja cech
reprezentacja hierarchiczna
Gabor filters
image retrieval
texture feature extraction
hierarchical representation
Opis:
Content Based Image Retrieval (CBIR) is now a widely investigated issue that aims at allowing users of multimedia information systems to automatically retrieve images coherent with a sample image. A way to achieve this goal is the computation of image features such as the color, texture, shape, and position of objects within images, and the use of those features as query terms. We propose to use Gabor filtration properties in order to find such appropriate features. The article presents multichannel Gabor filtering and a hierarchical image representation. Then a salient (characteristic) point detection algorithm is presented so that texture parameters are computed only in a neighborhood of salient points. We use Gabor texture features as image content descriptors and efficiently emply them to retrieve images.
Źródło:
International Journal of Applied Mathematics and Computer Science; 2005, 15, 4; 471-480
1641-876X
2083-8492
Pojawia się w:
International Journal of Applied Mathematics and Computer Science
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Novel visual object descriptor using surf and clustering algorithms
Autorzy:
Grycuk, R.
Powiązania:
https://bibliotekanauki.pl/articles/122762.pdf
Data publikacji:
2016
Wydawca:
Politechnika Częstochowska. Wydawnictwo Politechniki Częstochowskiej
Tematy:
k-means
mean shift
clustering
image description
SURF
keypoints
content-based image retrieval (CBIR)
opis obrazu
algorytmy grupowania
detekcja punktów kluczowych
Opis:
In this paper we propose a method for object description based on two wellknown clustering algorithms (k-means and mean shift) and the SURF method for keypoints detection. We also perform a comparison of these clustering methods in object description area. Both of these algorithms require one input parameter; k-means (k, number of objects) and mean shift (h, window). Our approach is suitable for images with a non-homogeneous background thus, the algorithm can be used not only on trivial images. In the future we will try to remove non-important keypoints detected by the SURF algorithm. Our method is a part of a larger CBIR system and it is used as a preprocessing stage.
Źródło:
Journal of Applied Mathematics and Computational Mechanics; 2016, 15, 3; 37-46
2299-9965
Pojawia się w:
Journal of Applied Mathematics and Computational Mechanics
Dostawca treści:
Biblioteka Nauki
Artykuł
Wyświetlanie 1-15 z 23

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