Particle shape analysis of tailings using digital image processing

2019 ◽  
Vol 26 (25) ◽  
pp. 26397-26403 ◽  
Author(s):  
Yonghao Yang ◽  
Zuoan Wei ◽  
Andy Fourie ◽  
Yulong Chen ◽  
Binbin Zheng ◽  
...  
Keyword(s):  
Image Processing ◽  
Digital Image Processing ◽  
Shape Analysis ◽  
Digital Image ◽  
Particle Shape

scholarly journals Automated Shape Analysis and DEM Study on Graded Crushed Stone

2021 ◽  
Vol 2021 ◽  
pp. 1-14
Author(s):  
Hao Bai ◽  
Ruidong Li ◽  
Xiangyu Hu ◽  
Fei Chen ◽  
Zhiyong Liao
Keyword(s):  
Image Processing ◽  
Deep Learning ◽  
Discrete Element Method ◽  
Digital Image Processing ◽  
Shape Analysis ◽  
Digital Image ◽  
Particle Shape ◽  
Void Ratio ◽  
Road Construction ◽  
Crushed Stone

Graded crushed stone (GCS), as a cheap and essential component, is of great importance in road construction. The irregularity and variability of particle shape is known to affect the packing characteristics of GCS, such as compactness and void ratio. In this study, the realistic particle outline is first automatically extracted based on digital image processing and deep learning algorithms. Then, the elongation (EI), roundness (Rd), and roughness (Rg) of GCS are quantified by shape evaluation algorithms. Moreover, based on the establishment of the GCS shape library, the gravity deposition with various elongations is simulated using the discrete element method to study the packing features of GCS. The elongation effects on the macroscopic and microscopic quantities are explored. Finally, the shear behavior of GCS is studied. The results illustrate that elongation has a significant effect on the packing of GCS.

Particle shape analysis of fine aggregate using a simplified digital image processing method

2013 ◽  
Vol 65 (1) ◽  
pp. 27-36 ◽  
Author(s):  
Luiz Roberto Prudêncio ◽  
Denis Fernandes Weidmann ◽  
Alexandre Lima de Oliveira ◽  
Gabriela Ferreira Damo
Keyword(s):  
Image Processing ◽  
Digital Image Processing ◽  
Shape Analysis ◽  
Digital Image ◽  
Particle Shape ◽  
Processing Method ◽  
Fine Aggregate ◽  
Image Processing Method

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.

Digital image processing methods applied to the study of annealing time on semiconductor-metal eutectic composites

1988 ◽  
Vol 46 ◽  
pp. 848-849
Author(s):  
J. Hefter
Keyword(s):  
Image Processing ◽  
Digital Image Processing ◽  
Digital Image ◽  
Electronic Device ◽  
Processing System ◽  
Average Diameter ◽  
Eutectic Solidification ◽  
Metal Silicide ◽  
The Matrix ◽  
Microscopic Studies

Semiconductor-metal composites, formed by the eutectic solidification of silicon and a metal silicide have been under investigation for some time for a number of electronic device applications. This composite system is comprised of a silicon matrix containing extended metal-silicide rod-shaped structures aligned in parallel throughout the material. The average diameter of such a rod in a typical system is about 1 μm. Thus, characterization of the rod morphology by electron microscope methods is necessitated.The types of morphometric information that may be obtained from such microscopic studies coupled with image processing are (i) the area fraction of rods in the matrix, (ii) the average rod diameter, (iii) an average circularity (roundness), and (iv) the number density (Nd;rods/cm2). To acquire electron images of these materials, a digital image processing system (Tracor Northern 5500/5600) attached to a JEOL JXA-840 analytical SEM has been used.

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