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Wyświetlanie 1-7 z 7
Tytuł:
Could k-NN classifier be Useful in tree leaves recognition?
Autorzy:
Horaisová, K.
Powiązania:
https://bibliotekanauki.pl/articles/229900.pdf
Data publikacji:
2014
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
binary image
Fourier transform
affine invariance
harmonic analysis
pattern recognition
k-NN classifier
Opis:
This paper presents a method for affine invariant recognition of two-dimensional binary objects based on 2D Fourier power spectrum. Such function is translation invariant and their moments of second order enable construction of affine invariant spectrum except of the rotation effect. Harmonic analysis of samples on circular paths generates Fourier coefficients whose absolute values are affine invariant descriptors. Affine invariancy is approximately saved also for large digital binary images as demonstrated in the experimental part. The proposed method is tested on artificial data set first and consequently on a large set of 2D binary digital images of tree leaves. High dimensionality of feature vectors is reduced via the kernel PCA technique with Gaussian kernel and the k-NN classifier is used for image classification. The results are summarized as k-NN classifier sensitivity after dimensionality reduction. The resulting descriptors after dimensionality reduction are able to distinguish real contours of tree leaves with acceptable classification error. The general methodology is directly applicable to any set of large binary images. All calculations were performed in the MATLAB environment.
Źródło:
Archives of Control Sciences; 2014, 24, 2; 177-192
1230-2384
Pojawia się w:
Archives of Control Sciences
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
IMAGE PATTERN ANALYSIS WITH IMAGE POTENTIAL TRANSFORM
Autorzy:
Oleg, Butusov
Dikusar, Vasily
Powiązania:
https://bibliotekanauki.pl/articles/452838.pdf
Data publikacji:
2018
Wydawca:
Szkoła Główna Gospodarstwa Wiejskiego w Warszawie. Katedra Ekonometrii i Statystyki
Tematy:
binary image transform
distance and potential transform
statistical indices
geometric signatures
pattern analysis
pattern recognition
Opis:
Pattern analysis with image transform based on potential calculation was considered. Initial gray-scale image is sliced into equidistant levels and resulting binary image was prepared by joining of some levels to one binary image. Binary image was transformed under assumption that white pixels in it may be considered as electric charges or spins. Using this assumption Ising model and Coulomb model interaction between white pixels was used for image potential transform. The transform was calculated using moving window. The resulting gray-scale image was again transformed to binary image using the thresholding on 0.5 level. Further binary images were analyzed using statistical indices (average, standard deviation, skewness, kurtosis) and geometric signatures: area, eccentricity, Euler number, orientation and perimeter. It was found that the most suitable geometric signature for pattern configuration analysis of Ising potential transform (IPT) and Coulomb potential transform (CPT) is area value. Similarly the most suitable statistics is distance statistics between white pixels.
Źródło:
Metody Ilościowe w Badaniach Ekonomicznych; 2018, 19, 1; 12-27
2082-792X
Pojawia się w:
Metody Ilościowe w Badaniach Ekonomicznych
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
A binary representation for real-valued, local feature descriptors
Autorzy:
Oszust, M.
Powiązania:
https://bibliotekanauki.pl/articles/384335.pdf
Data publikacji:
2017
Wydawca:
Sieć Badawcza Łukasiewicz - Przemysłowy Instytut Automatyki i Pomiarów
Tematy:
SIFT
SURF
LDAHash
binary tests
image matching
image recognition
Opis:
The usage of real-valued, local descriptors in computer vision applications is ofen constrained by their large memory requirements and long matching time. Typical approaches to the reduction of their vectors map the descriptor space to the Hamming space in which the obtained binary strings can be efficiently stored and compared. In contrary to such techniques, the approach proposed in this paper does not require a data-driven binarisation process, but can be seen as an extension of the floating-point descriptor computation pipeline with a step that allows turning it into a binary descriptor. In this step, binary tests are performed on values determined for pixel blocks from the described image patch. In the paper, the proposed approach is described and applied to two popular real-valued descriptors, SIFT and SURF. The paper also contains a comparison of the approach with state-of-the-art binarisation techniques and popular binary descriptors. The results demonstrate that the proposed representation for real-valued descriptors outperforms other methods on four demanding benchmark image datasets.
Źródło:
Journal of Automation Mobile Robotics and Intelligent Systems; 2017, 11, 1; 3-9
1897-8649
2080-2145
Pojawia się w:
Journal of Automation Mobile Robotics and Intelligent Systems
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:
The application of decision binary trees to assess the usefulness of the digital terrain model in studying the relationships between relief and vegetation in the Polish High Tatra
Autorzy:
Kącki, Karol
Powiązania:
https://bibliotekanauki.pl/articles/2030343.pdf
Data publikacji:
2006-06-01
Wydawca:
Uniwersytet Warszawski. Wydział Geografii i Studiów Regionalnych
Tematy:
relief - vegetation relationship
Decision Binary Trees (DBT)
Digital Terrain Model (DTM)
Ikonos XS
image classification
geoinformation
Opis:
The relationships between individual components of the natural environment have long been an object of research (Kostrowicki, Wójcik, 1972; Rączkowska, Kozłowska, 1994; Kozłowska, Rączkowska, 1996). This paper is an attempt to analyse the relationships between two geocomponents of the natural environment: relief and vegetation, from a perspective contrary to the one currently prevailing in the literature of the subject. This approach assumes that relief, with its dominant role as a component strongly affecting the formation of the remaining factors, can be indicative in character and as such can represent basie factors that help determine and anticipate the occurrences of certain plant communities as well as locations with no vegetation. Using geoinformation data along with the tools to process them, an attempt was made to assess the usefulness of the DTM (Digital Terrain Model) to identify selected plant communities, rock and water. The development of a model of the relationships between the relief and the vegetation is an attempt to capture the correspondence between the parameters characterising the relief, calcułated using the DTM model and classes of objects, with the use of information obtained from an Ikonos XS image. This model was subseąuently used to draw a map o f the land cover for a part of the Gąsienicowa Valley in the High Tatra (Dolina Gąsienicowa). For the purpose of this exercise, a techniąue of data classification called DBT (Decision Binary Trees) was used.
Źródło:
Miscellanea Geographica. Regional Studies on Development; 2006, 12; 305-313
0867-6046
2084-6118
Pojawia się w:
Miscellanea Geographica. Regional Studies on Development
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Obraz Polaków na podstawie komentarzy internautów po odwołanym meczu Polska–Anglia na Stadionie Narodowym w 2012 r.
Image of Polish people in the comments of internet users after the cancelation of the match Poland – England at the National Stadium in 2012
Autorzy:
Kuć, Joanna
Powiązania:
https://bibliotekanauki.pl/articles/38434466.pdf
Data publikacji:
2014-10-01
Wydawca:
Akademia Humanistyczno-Ekonomiczna w Łodzi
Tematy:
obraz Polaków
opozycja binarna
cechy Polaków
image of Polish people
binary opposition
features of Polish people
Opis:
Stereotypowy obraz Polaków wyraźnie ukazuje dwie grupy terminów i związanych z nimi komponentów. Pierwsza odnosi się do Polaków jako narodu, który łączą więzy krwi i terytorium. W tej sekcji przytoczono komentarze, ukazujące istotne cechy Polaków jako jednostki etnicznej, językowej, moralnej i kulturowej. Drugi obraz, oparty na binarnej opozycji nasz – obcy, ujawniającej wewnętrzne podziały narodowe, jest bardziej złożony i warstwowy. Twórcami tego modelu są różne osoby, które postrzegają polskość z różnych perspektyw, zgodnie ze swoimi potrzebami, uczuciami i doświadczeniami, co również relatywizuje odbiór. Tym bardziej można się spodziewać nie tylko jednego obrazu, przytaczanego przez odwołanie do meczu. Obie frakcje dają względne wyobrażenie o Polaku, które jest uzupełniane przez ocenę, niektóre wizje konkurują ze sobą, częściowo się pokrywając.
The stereotypical vision of Polish people clearly reveals two groups of terms and associated with them components, the first – referring to Polish as a nation, which combines ties of blood and territory. In this section, have been cited comments, showing the relevant features of Polish people as an ethnic, linguistic, moral and cultural units. The second image, based on a binary opposition our – a stranger, which reveals the internal national divisions, is more complex and stratified. The authors of this model are different people, who look back on Polishness from a variety of perspectives, according to their needs and feelings and experiences, which also relativizes the reception. The more you can expect not only the one picture cited by the match cancellation. Both factions give a relative idea of Polish man, which is completed by the assessment, some visions are in competition with each other, partly overlapping each other.
Źródło:
Językoznawstwo; 2014, 8; 39-46
1897-0389
2391-5137
Pojawia się w:
Językoznawstwo
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Robust content-based image retrieval using ICCV, GLCM, and DWT-MSLBP descriptors
Autorzy:
Chavda, Sagar
Goyani, Mahesh
Powiązania:
https://bibliotekanauki.pl/articles/27312841.pdf
Data publikacji:
2022
Wydawca:
Akademia Górniczo-Hutnicza im. Stanisława Staszica w Krakowie. Wydawnictwo AGH
Tematy:
content-based image retrieval
improved color coherence vector
gray-level co-occurrence matrix
discrete wavelet transform
multi-scale local binary pattern
principal component analysis
linear discriminant analysis
Opis:
Content-based image retrieval (CBIR) retrieves visually similar images from a dataset based on a specified query. A CBIR system measures the similarities between a query and the image contents in a dataset and ranks the dataset images. This work presents a novel framework for retrieving similar images based on color and texture features. We have computed color features with an improved color coherence vector (ICCV) and texture features with a gray-level co-occurrence matrix (GLCM) along with DWT-MSLBP (which is derived from applying a modified multi-scale local binary pattern [MS-LBP] over a discrete wavelet transform [DWT], resulting in powerful textural features). The optimal features are computed with the help of principal component analysis (PCA) and linear discriminant analysis (LDA). The proposed work uses a variancebased approach for choosing the number of principal components/eigenvectors in PCA. PCA with a 99.99% variance preserves healthy features, and LDA selects robust ones from the set of features. The proposed method was tested on four benchmark datasets with Euclidean and city-block distances. The proposed method outshines all of the identified state-of-the-art literature methods.
Źródło:
Computer Science; 2022, 23 (1); 5--36
1508-2806
2300-7036
Pojawia się w:
Computer Science
Dostawca treści:
Biblioteka Nauki
Artykuł
    Wyświetlanie 1-7 z 7

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