scholarly journals The complementary image

2020 ◽  
Vol 68 (1) ◽  
pp. 6
Author(s):  
MdShahid Alam ◽  
BhuvaneshwaranVedapuri Eswaran
Keyword(s):  
2018 ◽  
Vol 7 (3.4) ◽  
pp. 127
Author(s):  
Nagaraj Bhat ◽  
U Eranna ◽  
Manoj Kumar Singh

In this paper, a complementary approach has applied to obtain the available edges in the image. The complementary image has obtained by subtracting the rough mirror mapped image from the input image. The universal approximation capability of feedforward neural network has applied to define the rough mirror mapping. Multilayer perceptron network and radial basis function network have considered obtaining the mapping. Effect of better learning has also explored in both network by applying adaptivenesss in their transform function available in the active nodes. Single image based training has given for few number of iterations in the development of mapping process.  It is observed that proposed method has self adjusted content aware oriented edge detection where as many existing methods like Sobel, Prewitt have shown their limitations in observing the edges associated with contents having similar shade in the surroundings.  


Nature ◽  
1979 ◽  
Vol 279 (5713) ◽  
pp. 553-553 ◽  
Author(s):  
D. M. MACKAY
Keyword(s):  

2006 ◽  
Author(s):  
Chengxiang Liu ◽  
Xuejuan Hu ◽  
Yaobo Jian ◽  
Li Zhang
Keyword(s):  

1977 ◽  
Vol 60 (2) ◽  
pp. 289-296
Author(s):  
Leonora Auerbach

Abstract A comparative microscopic study of chrysotile fibers was conducted, using 3 sequential optical systems: plane polarized light (PL), phase contrast (PC), and Nomarski differential interference contrast (NDIC) for complementary image analyses. The introduction of NDIC for qualitative and quantitative analyses of particulate matter >5 μm resolves the problem of diffraction halos encountered in PC microscopy. High optical contrast, the instrumental characteristic of NDIC, is particularly useful for the detection of chrysotile fibers at a magnification of 500 ×.


Author(s):  
Євгенія Станіславівна Сулема ◽  
Семен Станіславович Широчин

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