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Wyświetlanie 1-15 z 57
Tytuł:
Notes on a linguistic description as the basis for automatic image understanding
Autorzy:
Tadeusiewicz, R.
Ogiela, M. R.
Szczepaniak, P. S.
Powiązania:
https://bibliotekanauki.pl/articles/907865.pdf
Data publikacji:
2009
Wydawca:
Uniwersytet Zielonogórski. Oficyna Wydawnicza
Tematy:
rozumienie automatyczne
widzenie komputerowe
obraz cyfrowy
semantyka
przetwarzanie obrazu
automatic understanding
computer vision
digital image
semantics
image processing
Opis:
The main paradigm of image understanding and a concept for its practical machine realisation are presented. The crucial elements of the presented approach are the formalisation of human knowledge about the class of images that are to be automatically interpreted, a linguistic description and the realization of cognitive resonance.
Źródło:
International Journal of Applied Mathematics and Computer Science; 2009, 19, 1; 143-150
1641-876X
2083-8492
Pojawia się w:
International Journal of Applied Mathematics and Computer Science
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
A proposition of mobile fractal image decompression
Autorzy:
Nikiel, S.
Powiązania:
https://bibliotekanauki.pl/articles/911258.pdf
Data publikacji:
2007
Wydawca:
Uniwersytet Zielonogórski. Oficyna Wydawnicza
Tematy:
fraktale
przetwarzanie obrazu
fraktalna kompresja obrazu
mobilne media
mapowanie tekstur
fractals
image processing
fractal image compression
mobile media
texture mapping
Opis:
Multimedia are becoming one of the most important elements of the user interface with regard to the acceptance of modern mobile devices. The multimodal content that is delivered and available for a wide range of mobile telephony terminals is indispensable to bind users to a system and its services. Currently available mobile devices are equipped with multimedia capabilities and decent processing power and storage area. The most crucial factors are then the bandwidth and costs of media transfer. This is particularly visible in mobile gaming, where textures represent the bulk of binary data to be acquired from the content provider. Image textures have traditionally added visual realism to computer graphics. The realism increases with the resolution of textures. This represents a challenge to the limited bandwidth of mobile-oriented systems. The challenge is even more obvious in mobile gaming, where single image depicts a collection of shots or animation cycles for sprites and a backdrop scenery. In order to increase the efficiency of image and image texture transfer, a fractal based compression scheme is proposed. The main idea is to use an asymmetric server-client architecture. The resource demanding compression process is performed on the server side while the client part decompresses highly packed image data. The method offers a very high compression ratio for pictures representing image textures for natural scenes. It aims to minimize the transmission bandwidth that should speed up the downloading process and minimize the cost and time of data transfer. The paper focuses on the implementation of fractal decompression schemes suitable for most mobile devices, and opens a discussion on fractal image models for limited resource applications.
Źródło:
International Journal of Applied Mathematics and Computer Science; 2007, 17, 1; 129-136
1641-876X
2083-8492
Pojawia się w:
International Journal of Applied Mathematics and Computer Science
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Implementation and evaluation of medical imaging techniques based on conformal geometric algebra
Autorzy:
Franchini, Silvia
Gentile, Antonio
Vassallo, Giorgio
Vitabile, Salvatore
Powiązania:
https://bibliotekanauki.pl/articles/329970.pdf
Data publikacji:
2020
Wydawca:
Uniwersytet Zielonogórski. Oficyna Wydawnicza
Tematy:
medical image segmentation
medical image registration
computational geometry
Clifford algebra
conformal geometric algebra
segmentacja obrazu
rejestracja obrazu medycznego
geometria obliczeniowa
algebra Clifforda
Opis:
Medical imaging tasks, such as segmentation, 3D modeling, and registration of medical images, involve complex geometric problems, usually solved by standard linear algebra and matrix calculations. In the last few decades, conformal geometric algebra (CGA) has emerged as a new approach to geometric computing that offers a simple and efficient representation of geometric objects and transformations. However, the practical use of CGA-based methods for big data image processing in medical imaging requires fast and efficient implementations of CGA operations to meet both real-time processing constraints and accuracy requirements. The purpose of this study is to present a novel implementation of CGA-based medical imaging techniques that makes them effective and practically usable. The paper exploits a new simplified formulation of CGA operators that allows significantly reduced execution times while maintaining the needed result precision. We have exploited this novel CGA formulation to re-design a suite of medical imaging automatic methods, including image segmentation, 3D reconstruction and registration. Experimental tests show that the re-formulated CGA-based methods lead to both higher precision results and reduced computation times, which makes them suitable for big data image processing applications. The segmentation algorithm provides the Dice index, sensitivity and specificity values of 98.14%, 98.05% and 97.73%, respectively, while the order of magnitude of the errors measured for the registration methods is 10-5.
Źródło:
International Journal of Applied Mathematics and Computer Science; 2020, 30, 3; 415-433
1641-876X
2083-8492
Pojawia się w:
International Journal of Applied Mathematics and Computer Science
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
An efficient algorithm for adaptive total variation based image decomposition and restoration
Autorzy:
Liu, X.
Huang, L.
Powiązania:
https://bibliotekanauki.pl/articles/330619.pdf
Data publikacji:
2014
Wydawca:
Uniwersytet Zielonogórski. Oficyna Wydawnicza
Tematy:
image decomposition
image restoration
adaptive total variation
H-1 norm
split Bregman method
dekompozycja obrazu
odtworzenie obrazu
wariacja zupełna adaptacyjna
metoda Bregmana
Opis:
With the aim to better preserve sharp edges and important structure features in the recovered image, this article researches an improved adaptive total variation regularization and H-1 norm fidelity based strategy for image decomposition and restoration. Computationally, for minimizing the proposed energy functional, we investigate an efficient numerical algorithm—the split Bregman method, and briefly prove its convergence. In addition, comparisons are also made with the classical OSV (Osher–Sole–Vese) model (Osher et al., 2003) and the TV-Gabor model (Aujol et al., 2006), in terms of the edge-preserving capability and the recovered results. Numerical experiments markedly demonstrate that our novel scheme yields significantly better outcomes in image decomposition and denoising than the existing models.
Źródło:
International Journal of Applied Mathematics and Computer Science; 2014, 24, 2; 405-415
1641-876X
2083-8492
Pojawia się w:
International Journal of Applied Mathematics and Computer Science
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Image based analysis of complex microstructures of engineering materials
Autorzy:
Wejrzanowski, T.
Spychalski, W. L.
Różniatowski, K.
Kurzydłowski, K. J.
Powiązania:
https://bibliotekanauki.pl/articles/908046.pdf
Data publikacji:
2008
Wydawca:
Uniwersytet Zielonogórski. Oficyna Wydawnicza
Tematy:
analiza obrazu
opis ilościowy
mikrostruktura
image analysis
quantitative description
microstructure
Opis:
The paper presents various methods for quantitative description of material structures. The main focus is on direct methods of description based on image analysis. In particular, techniques for the estimation of the size, shape and spatial distribution of structural elements observed by different microscopic techniques are described. The application of these methods for the characterization of the structures of engineering materials is demonstrated on a stainless steel used in petrochemical installations. It is shown that the methods applied are useful for the assessment of service degradation of materials.
Źródło:
International Journal of Applied Mathematics and Computer Science; 2008, 18, 1; 33-39
1641-876X
2083-8492
Pojawia się w:
International Journal of Applied Mathematics and Computer Science
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Parametric logarithmic type image processing for contrast based auto-focus in extreme lighting conditions
Autorzy:
Florea, C.
Florea, L.
Powiązania:
https://bibliotekanauki.pl/articles/329911.pdf
Data publikacji:
2013
Wydawca:
Uniwersytet Zielonogórski. Oficyna Wydawnicza
Tematy:
logarithmic image processing
digital camera
autofocus
logarytmiczne przetwarzanie obrazów
aparat cyfrowy
Opis:
While most of state-of-the-art image processing techniques were built under the so-called classical linear image processing, an alternative that presents superior behavior for specific applications comes in the form of Logarithmic Type Image Processing (LTIP). This refers to mathematical models constructed for the representation and processing of gray tones images. In this paper we describe a general mathematical framework that allows extensions of these models by various means while preserving their mathematical properties. We propose a parametric extension of LTIP models and discuss its similarities with the human visual system. The usability of the proposed extension model is verified for an application of contrast based auto-focus in extreme lighting conditions. The closing property of the named models facilitates superior behavior when compared with state-of-the-art methods.
Źródło:
International Journal of Applied Mathematics and Computer Science; 2013, 23, 3; 637-648
1641-876X
2083-8492
Pojawia się w:
International Journal of Applied Mathematics and Computer Science
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Breast cancer nuclei segmentation and classification based on a deep learning approach
Autorzy:
Kowal, Marek
Skobel, Marcin
Gramacki, Artur
Korbicz, Józef
Powiązania:
https://bibliotekanauki.pl/articles/1838197.pdf
Data publikacji:
2021
Wydawca:
Uniwersytet Zielonogórski. Oficyna Wydawnicza
Tematy:
breast cancer
nuclei segmentation
image processing
nowotwór piersi
segmentacja jądra
przetwarzanie obrazu
Opis:
One of the most popular methods in the diagnosis of breast cancer is fine-needle biopsy without aspiration. Cell nuclei are the most important elements of cancer diagnostics based on cytological images. Therefore, the first step of successful classification of cytological images is effective automatic segmentation of cell nuclei. The aims of our study include (a) development of segmentation methods of cell nuclei based on deep learning techniques, (b) extraction of some morphometric, colorimetric and textural features of individual segmented nuclei, (c) based on the extracted features, construction of effective classifiers for detecting malignant or benign cases. The segmentation methods used in this paper are based on (a) fully convolutional neural networks and (b) the marker-controlled watershed algorithm. For the classification task, seven various classification methods are used. Cell nuclei segmentation achieves 90% accuracy for benign and 86% for malignant nuclei according to the F-score. The maximum accuracy of the classification reached 80.2% to 92.4%, depending on the type (malignant or benign) of cell nuclei. The classification of tumors based on cytological images is an extremely challenging task. However, the obtained results are promising, and it is possible to state that automatic diagnostic methods are competitive to manual ones.
Źródło:
International Journal of Applied Mathematics and Computer Science; 2021, 31, 1; 85-106
1641-876X
2083-8492
Pojawia się w:
International Journal of Applied Mathematics and Computer Science
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Local detection of defects from image sequences
Autorzy:
Rafajłowicz, E.
Wnuk, M.
Rafajłowicz, W.
Powiązania:
https://bibliotekanauki.pl/articles/929862.pdf
Data publikacji:
2008
Wydawca:
Uniwersytet Zielonogórski. Oficyna Wydawnicza
Tematy:
przetwarzanie obrazu
wymiar fraktalny
operacje morfologiczne
image processing
fractal dimension
morphological operations
Opis:
Our aim is to discuss three approaches to the detection of defects in continuous production processes, which are based on local methods of processing image sequences. These approaches are motivated by and applicable to images of hot metals or other surfaces, which are uniform at a macroscopic level, when defects are not present. The first of them is based on the estimation of fractal dimensions of image cross-sections. The second and third approaches are compositions of known techniques, which are selected and tuned to our goal. We discuss their advantages and disadvantages, since they provide different information on defects. The results of their testing on 12 industrial images are also summarized.
Źródło:
International Journal of Applied Mathematics and Computer Science; 2008, 18, 4; 581-592
1641-876X
2083-8492
Pojawia się w:
International Journal of Applied Mathematics and Computer Science
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Picture Languages in Automatic Radiological Palm Interpretation
Autorzy:
Tadeusiewicz, R.
Ogiela, M. R.
Powiązania:
https://bibliotekanauki.pl/articles/908539.pdf
Data publikacji:
2005
Wydawca:
Uniwersytet Zielonogórski. Oficyna Wydawnicza
Tematy:
komputerowe wspomaganie diagnozy
diagnostyka choroby
choroba dłoni
syntaktyczne rozpoznawanie obrazu
rozumienie obrazu
medyczna analiza obrazu
syntactic pattern recognition
image understanding
medical image analysis
computer-aided diagnosis
palm disease diagnostics
Opis:
The paper presents a new technique for cognitive analysis and recognition of pathological wrist bone lesions. This method uses AI techniques and mathematical linguistics allowing us to automatically evaluate the structure of the said bones, based on palm radiological images. Possibilities of computer interpretation of selected images, based on the methodology of automatic medical image understanding, as introduced by the authors, were created owing to the introduction of an original relational description of individual palm bones. This description was built with the use of graph linguistic formalisms already applied in artificial intelligence. The research described in this paper demonstrates that for the needs of palm bone diagnostics, specialist linguistic tools such as expansive graph grammars and EDT-label graphs are particularly well suited. Defining a graph image language adjusted to the specific features of the scientific problem described here permitted a semantic description of correct palm bone structures. It also enabled the interpretation of images showing some in-born lesions, such as additional bones or acquired lesions such as their incorrect junctions resulting from injuries and synostoses.
Źródło:
International Journal of Applied Mathematics and Computer Science; 2005, 15, 2; 305-312
1641-876X
2083-8492
Pojawia się w:
International Journal of Applied Mathematics and Computer Science
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Image cipher applications using the elliptical curve and chaos
Autorzy:
Silva-García, Víctor Manuel
Flores-Carapia, Rolando
Rentería-Márquez, Carlos
Luna-Benoso, Bejamín
Chimal-Eguía, Juan Carlos
Powiązania:
https://bibliotekanauki.pl/articles/329867.pdf
Data publikacji:
2020
Wydawca:
Uniwersytet Zielonogórski. Oficyna Wydawnicza
Tematy:
elliptic curve
chaos
discrete Fourier transform
image ciphering
krzywa eliptyczna
dyskretna transformata Fouriera
Opis:
A novel symmetric cryptosystem of the substitution permutation network type is presented for image encryption in 14 rounds. An algorithm is developed to generate 15 keys to encrypt images where each key is the image size. These keys are calculated using an elliptic curve with a constant zero value. The proposed curve is non-singular, non-supersingular, nor trace one. Chaos is employed to find a generating element in a cyclic subgroup and it is produced using the logistic map equation. In addition, a 16 × 16 substitution box is constructed using both chaos and an algorithm that defines a bijective function. The following tools are used in order to measure the degree of randomness of the encrypted figures: entropy, correlation, the discrete Fourier transform and a goodness-of-fit test with the chi-square distribution. Furthermore, an image size variable permutation is applied in the first round, and its inverse in the fourteenth.
Źródło:
International Journal of Applied Mathematics and Computer Science; 2020, 30, 2; 377-391
1641-876X
2083-8492
Pojawia się w:
International Journal of Applied Mathematics and Computer Science
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Nonlinear image processing and filtering: a unified approach based on vertically weighted regression
Autorzy:
Rafajłowicz, E.
Pawlak, M.
Steland, A.
Powiązania:
https://bibliotekanauki.pl/articles/908044.pdf
Data publikacji:
2008
Wydawca:
Uniwersytet Zielonogórski. Oficyna Wydawnicza
Tematy:
filtr nieliniowy
filtracja obrazu
regresja ważona
image filtering
vertically weighted regression
nonlinear filters
Opis:
A class of nonparametric smoothing kernel methods for image processing and filtering that possess edge-preserving properties is examined. The proposed approach is a nonlinearly modified version of the classical nonparametric regression estimates utilizing the concept of vertical weighting. The method unifies a number of known nonlinear image filtering and denoising algorithms such as bilateral and steering kernel filters. It is shown that vertically weighted filters can be realized by a structure of three interconnected radial basis function (RBF) networks. We also assess the performance of the algorithm by studying industrial images.
Źródło:
International Journal of Applied Mathematics and Computer Science; 2008, 18, 1; 49-61
1641-876X
2083-8492
Pojawia się w:
International Journal of Applied Mathematics and Computer Science
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Classification of high resolution satellite images using improved U-Net
Autorzy:
Wang, Yong
Zhang, Dongfang
Dai, Guangming
Powiązania:
https://bibliotekanauki.pl/articles/331235.pdf
Data publikacji:
2020
Wydawca:
Uniwersytet Zielonogórski. Oficyna Wydawnicza
Tematy:
satellite image classification
deep learning
U-net
spatial pyramid pooling
zdjęcia satelitarne
uczenie głębokie
Opis:
Satellite image classification is essential for many socio-economic and environmental applications of geographic information systems, including urban and regional planning, conservation and management of natural resources, etc. In this paper, we propose a deep learning architecture to perform the pixel-level understanding of high spatial resolution satellite images and apply it to image classification tasks. Specifically, we augment the spatial pyramid pooling module with image-level features encoding the global context, and integrate it into the U-Net structure. The proposed model solves the problem consisting in the fact that U-Net tends to lose object boundaries after multiple pooling operations. In our experiments, two public datasets are used to assess the performance of the proposed model. Comparison with the results from the published algorithms demonstrates the effectiveness of our approach.
Źródło:
International Journal of Applied Mathematics and Computer Science; 2020, 30, 3; 399-413
1641-876X
2083-8492
Pojawia się w:
International Journal of Applied Mathematics and Computer Science
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
A new approach to image reconstruction from projections using a recurrent neural network
Autorzy:
Cierniak, R.
Powiązania:
https://bibliotekanauki.pl/articles/907945.pdf
Data publikacji:
2008
Wydawca:
Uniwersytet Zielonogórski. Oficyna Wydawnicza
Tematy:
rekonstrukcja obrazu
sieć neuronowa
sieć rekurencyjna
image reconstruction from projections
neural networks
recurrent net
Opis:
A new neural network approach to image reconstruction from projections considering the parallel geometry of the scanner is presented. To solve this key problem in computed tomography, a special recurrent neural network is proposed. The reconstruction process is performed during the minimization of the energy function in this network. The performed computer simulations show that the neural network reconstruction algorithm designed to work in this way outperforms conventional methods in the obtained image quality.
Źródło:
International Journal of Applied Mathematics and Computer Science; 2008, 18, 2; 147-157
1641-876X
2083-8492
Pojawia się w:
International Journal of Applied Mathematics and Computer Science
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Denseformer for single image deraining
Autorzy:
Wang, Tianming
Wang, Kaige
Li, Qing
Powiązania:
https://bibliotekanauki.pl/articles/24987759.pdf
Data publikacji:
2023
Wydawca:
Uniwersytet Zielonogórski. Oficyna Wydawnicza
Tematy:
artificial intelligence
convolutional neural network
image deraining
sztuczna inteligencja
sieć neuronowa konwolucyjna
obraz pojedynczy
Opis:
Image is one of the most important forms of information expression in multimedia. It is the key factor to determine the visual effect of multimedia software. As an image restoration task, image deraining can effectively restore the original information of the image, which is conducive to the downstream task. In recent years, with the development of deep learning technology, CNN and Transformer structures have shone brightly in computer vision. In this paper, we summarize the key to success of these structures in the past, and on this basis, we introduce the concept of a layer aggregation mechanism to describe how to reuse the information of the previous layer to better extract the features of the current layer. Based on this layer aggregation mechanism, we build the rain removal network called DenseformerNet. Our network strengthens feature promotion and encourages feature reuse, allowing better information and gradient flow. Through a large number of experiments, we prove that our model is efficient and effective, and expect to bring some illumination to the future rain removal network.
Źródło:
International Journal of Applied Mathematics and Computer Science; 2023, 33, 4; 651--661
1641-876X
2083-8492
Pojawia się w:
International Journal of Applied Mathematics and Computer Science
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
Wyświetlanie 1-15 z 57

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