Determination of pore size parameters and its distribution of hydroentangled fabrics by image processing

2008 ◽  
Vol 99 (4) ◽  
pp. 317-324 ◽  
Author(s):  
V. K. Kothari ◽  
Gaurav Agarwal
Keyword(s):  
Image Processing ◽  
Pore Size

Information and estimation in image processing

1987 ◽  
Vol 45 ◽  
pp. 14-17
Author(s):  
B. Roy Frieden
Keyword(s):  
Image Processing ◽  
Optical System ◽  
Large Amplitude ◽  
Communication Theory ◽  
Image Data ◽  
Direct Approach ◽  
Ill Posed

Despite the skill and determination of electro-optical system designers, the images acquired using their best designs often suffer from blur and noise. The aim of an “image enhancer” such as myself is to improve these poor images, usually by digital means, such that they better resemble the true, “optical object,” input to the system. This problem is notoriously “ill-posed,” i.e. any direct approach at inversion of the image data suffers strongly from the presence of even a small amount of noise in the data. In fact, the fluctuations engendered in neighboring output values tend to be strongly negative-correlated, so that the output spatially oscillates up and down, with large amplitude, about the true object. What can be done about this situation? As we shall see, various concepts taken from statistical communication theory have proven to be of real use in attacking this problem. We offer below a brief summary of these concepts.

The quantitative comparison of experimental and simulated diffraction contrast images

1995 ◽  
Vol 53 ◽  
pp. 102-103
Author(s):  
Stuart McKernan
Keyword(s):  
Image Processing ◽  
Personal Computer ◽  
Close Agreement ◽  
Quantitative Comparison ◽  
Image Simulation ◽  
Computing Power ◽  
Diffraction Contrast ◽  
Simulated Images ◽  
Made In

For many years the concept of quantitative diffraction contrast experiments might have consisted of the determination of dislocation Burgers vectors using a g.b = 0 criterion from several different 2-beam images. Since the advent of the personal computer revolution, the available computing power for performing image-processing and image-simulation calculations is enormous and ubiquitous. Several programs now exist to perform simulations of diffraction contrast images using various approximations. The most common approximations are the use of only 2-beams or a single systematic row to calculate the image contrast, or calculating the image using a column approximation. The increasing amount of literature showing comparisons of experimental and simulated images shows that it is possible to obtain very close agreement between the two images; although the choice of parameters used, and the assumptions made, in performing the calculation must be properly dealt with. The simulation of the images of defects in materials has, in many cases, therefore become a tractable problem.

Determination of the pore size of woven structures through image analysis

2012 ◽  
Vol 2 (1) ◽  
Author(s):  
R. Angelova
Keyword(s):  
Pore Size ◽  
Single Layer ◽  
Woven Fabric ◽  
Virtual Model ◽  
Experimental Procedure ◽  
Porosity And Permeability ◽  
Woven Structures ◽  
Woven Structure ◽  
Non Destructive

AbstractThe paper presents an experimental procedure developed for determination of the pore size, shape and distribution in a single layer woven fabric, for the construction of a virtual model to be incorporated in a future CFD software package. The procedure is based on non-destructive observation and analysis of woven samples. 14 different samples of gray fabrics of 100 % cotton in plain and twill weaves are investigated. The results obtained allow the creation of reality more realistic virtual model of the woven structure, and theoretical investigation of its porosity and permeability through computer simulation.

DETERMINATION OF POROSITY CONTENT IN COMPOSITES BY MICROGRAPH IMAGE PROCESSING

2008 ◽  
Author(s):  
A. H. Kite ◽  
D. K. Hsu ◽  
D. J. Barnard ◽  
Donald O. Thompson ◽  
Dale E. Chimenti
Keyword(s):  
Image Processing
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