Prediction of grain boundary of a composite microstructure using digital image processing: A comparative study

2020 ◽  
Author(s):  
Sweta Rani Biswal ◽  
Tapasmini Sahoo ◽  
Seshadev Sahoo
Keyword(s):  
Image Processing ◽  
Grain Boundary ◽  
Comparative Study ◽  
Digital Image Processing ◽  
Digital Image ◽  
Composite Microstructure

Phase-shifting methodologies in photoelastic analysis—the application of Jones calculus

1996 ◽  
Vol 31 (6) ◽  
pp. 423-432 ◽  
Author(s):  
K Ramesh ◽  
V Ganapathy
Keyword(s):  
Image Processing ◽  
Stress Concentration ◽  
Data Collection ◽  
Comparative Study ◽  
Digital Image Processing ◽  
Digital Image ◽  
Phase Shifting ◽  
Intensity Data ◽  
New Approach ◽  
Photoelastic Analysis

The potential of digital image processing hardware to record intensity data at video rates has resulted in a new approach for data collection. Efforts were aimed at evaluating isochromatic and isoclinic fringe orders quantitatively by processing the intensity data recorded. These methodologies have come to be known as phase-shifting techniques. The various phase-shifting algorithms in photoelasticity are surveyed and a comparative study is done. The use of Jones calculus to understand these methodologies is brought out. An attempt has been made to identify the reason for loss of accuracy in evaluating the field parameters in stress concentration zones.

scholarly journals A COMPARATIVE STUDY OF COMMON EDGE DETECTION OPERATORS IN DIGITAL IMAGE PROCESSING

2021 ◽  
Vol 6 (4) ◽  
pp. 147-152
Author(s):  
Benjamin Kommey ◽  
John Kwame Dunyo ◽  
Eric Tutu Tchao ◽  
Andrew Selasi Agbemenu
Keyword(s):  
Image Processing ◽  
Edge Detection ◽  
Comparative Study ◽  
Digital Image Processing ◽  
Digital Image ◽  
Common Edge

scholarly journals Comparative study of image enhancement techniques using histogram equalization on degraded images

2018 ◽  
Vol 7 (2.8) ◽  
pp. 468 ◽  
Author(s):  
Shalika Arora ◽  
Megha Agarwal ◽  
Veepin Kumar ◽  
Divya Gupta
Keyword(s):  
Image Processing ◽  
Comparative Study ◽  
Image Enhancement ◽  
Digital Image Processing ◽  
Digital Image ◽  
Histogram Equalization ◽  
Vital Role ◽  
Enhancement Technique ◽  
Degraded Images

Image Enhancement technique plays a vital role in digital image processing for making an image to be useful for various applications. This technique is used to improve the quality of degraded images.Usually, the degradation is not evenly spread throughout the image, but most of the time it varies from region to region. Our aim is to first identify the region where enhancement is required and improve that region without disturbing its neighbourhood which does not require any improvement. 

An Overview of Digital Image Processing and Recognition (Invited Paper)

1982 ◽  
Vol 40 ◽  
pp. 700-702
Author(s):  
R. C. Gonzalez
Keyword(s):  
Image Processing ◽  
New York ◽  
Digital Image Processing ◽  
Digital Image ◽  
Practical Implementation ◽  
Submarine Cable ◽  
Vigorous Growth ◽  
Digitized Pictures ◽  
Processing Techniques ◽  
And Storage

Interest in digital image processing techniques dates back to the early 1920's, when digitized pictures of world news events were first transmitted by submarine cable between New York and London. Applications of digital image processing concepts, however, did not become widespread until the middle 1960's, when third-generation digital computers began to offer the speed and storage capabilities required for practical implementation of image processing algorithms. Since then, this area has experienced vigorous growth, having been a subject of interdisciplinary research in fields ranging from engineering and computer science to biology, chemistry, and medicine.

A method to measure pores and fissures in geologic materials under S.E.M. by digital image processing

1978 ◽  
Vol 36 (1) ◽  
pp. 212-213
Author(s):  
L. Montoto ◽  
M. Montoto ◽  
A. Bel-Lan
Keyword(s):  
Image Processing ◽  
Optical Microscopy ◽  
Digital Image Processing ◽  
Digital Image ◽  
Digital Processing ◽  
Free Surfaces ◽  
Geologic Materials ◽  
Automatic Information ◽  
Detector Output ◽  
Rock Specimens

INTRODUCTION.- The physical properties of rock masses are greatly influenced by their internal discontinuities, like pores and fissures. So, these need to be measured as a basis for interpretation. To avoid the basic difficulties of measurement under optical microscopy and analogic image systems, the authors use S.E.M. and multiband digital image processing. In S.E.M., analog signal processing has been used to further image enhancement (1), but automatic information extraction can be achieved by simple digital processing of S.E.M. images (2). The use of multiband image would overcome difficulties such as artifacts introduced by the relative positions of sample and detector or the typicals encountered in optical microscopy.DIGITAL IMAGE PROCESSING.- The studied rock specimens were in the form of flat deformation-free surfaces observed under a Phillips SEM model 500. The SEM detector output signal was recorded in picture form in b&w negatives and digitized using a Perkin Elmer 1010 MP flat microdensitometer.

Sign in / Sign up

Export Citation Format

Share Document