Particle Shape Analysis Using Digital Image Processing
Fillipe Souza Silva2018
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The fluidization technology has been closely related to traditional processes, such as petrochemical, pharmaceutical, polymer, food, and incineration (Kunii & Levenspiel, 1991). In these processes, the characterization of solid particles is vital to obtain higher efficiencies and lower process costs. Recently, many clean energy processes (e.g.: mechanical processes, pyrolysis, combustion, and gasification) involving biomass (non-woody and woody plants, and organic wastes) need fundamental parameters to understand energy conversion (physical, chemical, thermal and biological) in obtaining bio-fuels (gas, liquid or solid), electricity or heat. All of them require versatility in a wide range of chemical reactor configurations and designs (Cui & Grace, 2007;-Dai & Grace, 2011; Tannous e Lourenço, 2015). Fundamental parameters are necessary to understand the dynamic behavior of solids in these reactors because the particles have irregular non-spherical shapes. According to Guo, Chen, and...
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Category: Computer Vision and Image Processing
Particle Shape Analysis Using
Digital Image Processing
Katia Tannous
University of Campinas, Brazil
Fillipe Souza Silva
University of Campinas, Brazil
INTRODUCTION
The fluidization technology has been closely related to traditional processes, such as petrochemical,
pharmaceutical, polymer, food, and incineration
(Kunii & Levenspiel, 1991). In these processes,
the characterization of solid particles is vital to
obtain higher efficiencies and lower process costs.
Recently, many clean energy processes (e.g.:
mechanical processes, pyrolysis, combustion, and
gasification) involving biomass (non-woody and
woody plants, and organic wastes) need fundamental parameters to understand energy conversion
(physical, chemical, thermal and biological) in
obtaining bio-fuels (gas, liquid or solid), electricity or heat. All of them require versatility in
a wide range of chemical reactor configurations
and designs (Cui & Grace, 2007;-Dai & Grace,
2011; Tannous e Lourenço, 2015).
Fundamental parameters are necessary to
understand the dynamic behavior of solids in
these reactors because the particles have irregular
non-spherical shapes. According to Guo, Chen,
and Liu (2012), biomass particles are extremely
irregular due to their high contents of cellulose,
hemicellulose and lignin. Mandø and Rosendahl
(2010), and also, Tannous, Lam, Sokhansanj, and
Grace (2013) reviewed fundamental definitions for
solid particles such as mean diameter and shape.
Different definitions have been presented in
the literature to calculate shape factors of solid
particles based on two-dimensional (2D) and
three-dimensional (3D) analyses. Depending on
the shape, two-dimension representations may be
insufficient to represent the true particle shapes
(Zavala, 2012; Rodriguez, Edeskär, & Knutsson,
2013; Tannous, Lam, Sokhansanj, & Grace, 2013).
The geometry of biomass particles is complex
because it depends of the type of raw material and
process applied changing its size and shape from
the beginning to the end of the process (Dai &
Grace, 2011). There is a need to develop appropriate geometrical definitions as well as algorithms to
describe particles shapes (Rodriguez, Johansson,
& Edeskär, 2012).
This chapter will discuss new software, Particles and Geometric Shapes Analyzer (APOGEO)
aiming the determination of major and minor
axes, aspect ratio and sphericity of solid particles
(mainly biomass) for four different definitions
by image processing without any manual work.
This software was developed to reach users from
academy and industry.
BACKGROUND
The influence of biomass particle shapes cannot
be ignored in particle transportation, mixing and
fluidization processes. Various particle shapes
result in different particle surface areas, in which
are heat and mass transfer processes (Guo et al.,
2012). Rodriguez et al. (2013) have presented a
review about different methods and techniques to
determine the geometrical shape of the particles.
The authors observed that there is no agreement
DOI: 10.4018/978-1-5225-2255-3.ch114
Copyright © 2018, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited.
C
Particle Shape Analysis Using Digital Image Processing
on the usage of the descriptors and is not clear
which descriptor is the best. A large scale shape
classification has been a problem. In addition,
the authors considered that image analysis is a
promising tool; it presents advantages like low
time consumption or repeatability.
When non-spherical solid particles are observed through a microscope, various methods
can be used for their sizing, resulting in terms
of an equivalent spherical particle. Projected
images in microscopes (optical, scanning and
transmission) are in two-dimensional and depend
on the orientation of the particles (Turbitt-Daoust,
Alliet, Kaye, & Matchett, 2000). Particles in a
stable orientation tend to have a maximum area
causing microscopic measurements larger values
than those presented by other methods, i.e., when
smaller particle sizes are discarded.
This technique requires the analysis of a number of particles statistically significant, which
has needed the use of automatic image analysis
programs, conducted with the aid of computers
and specific software. This process includes several steps: 1) acquisition and image scanning, 2)
pre- and post-processing of the scanned image, 3)
measurements (shape, size and count), 4) analysis
and data presentation (Papini, 2003).
Currently, different equipments can be found
on the market, but a few of them can be use for
biomass particles, for example: Olympus BX51
from Olympus Corporation; Morphologi G3 and
Sysmex FPA3000 from Malvern Instruments Ltd;
Camsizer and Camsizer XT from Retsch Technology GmbH; CILAS granulometer and expert
Shape from Compagnie Industrielle des Lasers;
Nikon E200 and ImagemJ software, DOMAS
Digital Imaging System from Fiber and Particle
Engineering Laboratory (University of Oulu),
and Eyecon™ from Innopharma Labs. These
equipments calculate, in general, the aspect ratio,
the roundness, the convexity, the elongation, and
the linearity of the materials. Remarking that, the
quality of the results is dependent on the skill and
experience of the operator, and also the correct
calibration of the microscope.
1332
In view of the impossibility of obtain such equipments for economic reasons, in 2011, Tannous and
Silva (2012) have decided to seek alternatives to
solve many research problems concerning biomass
particles through of development of their own
software to obtain the shape and sphericity of these
kind of particles. This laboratory has experience in
educational software development (Rimoli, Assis,
& Tannous, 2006; Maranesi & Tannous, 2009;
Tannous & Rocha, 2012; Tannous & Santos, 2012).
DEVELOPMENT OF
APOGEO® SOFTWARE
General Information
APOGEO® (Particles and Geometric Shapes
Analyzer) software was developed to reach
professionals in different area of expertise (e.g:
chemist; physicist; and chemical, mechanical and
food engineers). It is based on image processing
technique in order to transform pixels in computational objects. This software was published in
the National Institute of Industrial Property-Brazil
(nº 13085-6) by Tannous and Silva (2012).
The software can quantify the major and minor axes correlating two or three dimensions of
particles (e.g.: woods, coconut fiber, sugarcane
bagasse, and rice husk) to obtain its sphericity.
The particles can be associated with different
geometries such as: rectangular parallelepiped,
cylinder, oblate and prolate spheroids, and irregular. The results are presented in histograms
and tables, but also can be saved in a spreadsheet
(Excel file, OpenOffice Calc file).
Minimum Hardware Requirements
APOGEO was developed on personal computer
sufficiently supplied with memory and processing
of operational systems. The hardware chosen was
a processor of 800 MHz, 1 GB of RAM memory,
monitor of 15”, mouse, keyboard, and Java Runtime Environment (version 1.6.0 or higher).
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