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Wyszukujesz frazę "optical microscopy" wg kryterium: Temat


Wyświetlanie 1-2 z 2
Tytuł:
Moving-aperture-based three-dimensional micro-measurement system
Autorzy:
Fan, S.
Yu, M.
Jiang, G.
Wang, Y.
Wang, W.
Li, W.
Powiązania:
https://bibliotekanauki.pl/articles/174026.pdf
Data publikacji:
2018
Wydawca:
Politechnika Wrocławska. Oficyna Wydawnicza Politechniki Wrocławskiej
Tematy:
optical microscopy
computational photography
three-dimensional micro-measurement
moving aperture
Opis:
To overcome the depth-of-field limitation of an optical microscope image, a three-dimensional measurement method with a superior depth-of-field is proposed. In the proposed method, light-field information of different angles is obtained by moving the aperture and the three-dimensional scene is reconstructed by using a computational reconstruction technology. First, stereo matching of different aperture position images is performed to obtain the multi-aperture imaging deviation. The focal plane moving distance is thereby estimated. Then, the relational expression between the image coordinates and the focal plane moving distance is determined according to the image coordinates. Two dimensional coordinates of the space point are obtained by the expression coefficients. Finally, the depth coordinates are computed, and three-dimensional reconstruction of the spatial points is completed. Experiments of three-dimensional measurements of the calibration board with different angles and circuit boards are conducted. The results show that the maximum error of the distance measurement is controlled into 0.84%, and the maximum angle measurement error is controlled into 4.56%.
Źródło:
Optica Applicata; 2018, 48, 4; 533-547
0078-5466
1899-7015
Pojawia się w:
Optica Applicata
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Graph-based segmentation with homogeneous hue and texture vertices
Autorzy:
Ngo, Lua
Han, Jae-Ho
Powiązania:
https://bibliotekanauki.pl/articles/2033896.pdf
Data publikacji:
2021
Wydawca:
Politechnika Wrocławska. Oficyna Wydawnicza Politechniki Wrocławskiej
Tematy:
image segmentation
deep neural network
electron microscopy
optical coherence tomography
pattern recognition
Opis:
This work presents an automated segmentation method, based on graph theory, which processes superpixels that exhibit spatially similarities in hue and texture pixel groups, rather than individual pixels. The graph shortest path includes a chain of neighboring superpixels which have minimal intensity changes. This method reduces graphics computational complexity because it provides large decreases in the number of vertices as the superpixel size increases. For the starting vertex prediction, the boundary pixel in first column which is included in this starting vertex is predicted by a trained deep neural network formulated as a regression task. By formulating the problem as a regression scheme, the computational burden is decreased in comparison with classifying each pixel in the entire image. This feasibility approach, when applied as a preliminary study in electron microscopy and optical coherence tomography images, demonstrated high measures of accuracy: 0.9670 for the electron microscopy image and 0.9930 for vitreous/nerve-fiber and inner-segment/outer-segment layer segmentations in the optical coherence tomography image.
Źródło:
Optica Applicata; 2021, 51, 4; 541-549
0078-5466
1899-7015
Pojawia się w:
Optica Applicata
Dostawca treści:
Biblioteka Nauki
Artykuł
    Wyświetlanie 1-2 z 2

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