METHOD AND APPARATUS FOR IMAGING BASED SIZE
CHARACTERIZATION OF GREEN BALLS IN PELLET PLANT
FIELD OF INVENTION:
[001] The present subject matter described herein, relates to a size
characterization of green balls in pellet plant of steelmaking industry and, in
particular, to an automatic size characterization of plurality of green balls being
fed into an induration furnace using image processing techniques.
BACKGROUND AND PRIOR ART AND PROBLEM IN PRIOR ART:
[002] Pelletizing of iron ore was started in the 1950s to facilitate the utilization
of finely ground iron ore concentrates in steel production. In the pelletization
process comprises two main stages (1) agglomeration and (2) induration. During
agglomeration, finely ground particulates of ore concentrate with a moisture
content are mixed with additives and binders and sent to the balling drums or
discs where the forces act between the particle grains to create a bonded pellet
referred to in the industry as a “green ball. The green balls formed during the
agglomeration process are strong enough for transport to induration machine. The
green pellets are subjected to certain varying process zones of drying, preheating,
firing and cooling. Each zone varies by temperature and residence time in order to
ensure that all bonds and mineral bridging is formed, strengthening and heat
hardening each green ball into an indurated pellet product which is then suitable
for feed in the steel making process.
[003] There are two main types of processes, the Straight Grate and the Grate
Kiln processes. In the Straight Grate process, a stationary bed of pellets is
transported on an endless travelling grate through the drying, oxidation, sintering
and cooling zones. In the Grate Kiln process, drying and most of the oxidation is
accomplished in a stationary pellet bed. Thereafter, pellets are loaded in a rotary
kiln for sintering. In this way, more homogenous induration in pellets is achieved.
Grate-kiln systems are consistently of higher quality than those produced in a

straight grate. Rotary kiln of the Grate kiln process provides constant mixing of
the pellets and bringing all the pellets to the same temperature.
[004] Green pellets manufacture during the agglomeration process are different
size. During agglomeration, variations occur in the properties of the incoming
pellet feed, like moisture content, fineness and wettability, which result in
fluctuations in the green pellet growth rate and size distribution. Hence, knowing
the size distribution of green pellets is important for appropriate control.
Disturbances in balling give rise to increasing recycling loads and pulsation in the
production rate of the on-size green pellet fraction (surging). Excessive surging
causes problems not only in the balling circuits but also in the induration machine.
Disturbances in the pellet size distribution are regulated either mechanically, by
adjusting the screen openings for the recycling load or for the on-size fraction, or
“chemically” by slightly varying the moisture content or the binder dosage.
Therefore, a narrow size distribution in green pellets is an important criterion for
the pellet quality, because high permeability in a bed of pellets is beneficial for
both the pellet production process and the subsequent reduction process in
steelmaking.
[005] Conventionally, there are several prior art techniques for measuring the
size and distribution of sizes of particles in a sample by using light scattering.
Generally, to measure the sizes of individual particles, for example, in a flowing
stream of a liquid or gas, the particle-containing sample stream is illuminated by a
constant light source and the intensity of light scattered by each particle is
detected.
[006] In general, larger particles scatter more light corresponds to smaller
particles. A particle scatters the light by an amount related to the particle size. The
relationship between the amount of scattering and particle size can be determined
either from theoretical calculations. With knowledge of this relationship, for a
single particle at a time, the detected scattered light intensity provides a direct
measure of the particle size. The distribution of particle sizes in a sample can be
determined by individually passing each particle in the sample, or a portion of the

sample, through the scattered light detection apparatus, and tabulating the sizes of
the various particles. In practice, this method is generally restricted to particles
larger than 0.5 microns. Moreover, this method is relatively slow, because
particles must be presented and detected individually. This technique is referred to
in the prior art as optical particle counting.
[007] In another prior art technique of particle sizing by light scattering is
referred to as static or "classical" light scattering. This method is based upon
illumination of a sample containing the particles to be sized, followed by the
measurement of the intensity of scattered light at several predetermined angles.
The intensity of light scattered from a particle is a function of the size of the
particle, the wavelength of incident light, and the angle at which the scattered light
is collected relative to the incident light. This method of particle sizing based
upon the angular dependence of the scattered light intensity can be employed to
determine the size distribution of a group of particles.
[008] Generally temperature around the induration furnace is very high
approximately more than 100o C. Further, environment near the induration
furnace is very dusty. In the dusty area, image quality of the green balls is not
good. Further, there is one major challenge in the image processing system is to
protect the camera device and the lighting device from the high temperature and
the dust.
[009] Green pellets with uneven size effects the quality and efficiency of the
induration process and steelmaking process at the end. Therefore, it is necessary
to provide a method for size characterization of the green balls to be fed into the
induration furnace.
OBJECTS OF THE INVENTION:
[0010] The principal objective of the present invention is to provide an apparatus
for automatic size characterization of green balls/pellets to be fed into the
induration furnace.

[0011] Another object of the present invention is to provide a camera over the
conveyer belt of the induration furnace, where enclosure of the camera is designed
in such a manner that cools the camera and lighting assembly while also purging
the faces of the camera and lighting assemblies for better viewing and
illumination capabilities.
[0012] Another object of the present invention is to provide an image acquisition
system to process the captured image and determine the size of the green pellets.
[0013] Yet another object of the present invention is to provide a method for
automatic size characterization of green balls to be fed into the induration furnace
using image processing techniques by image acquisition system.
SUMMARY OF THE INVENTION:
[0014] The present subject matter relates a method and system for automatic size
characterization of plurality of green balls being fed into an induration furnace
using image processing techniques. The system includes an imaging device and
illumination device which is installed above conveyor belt in the pellet plant. The
imaging device takes the images of plurality of green pellets lying on the
conveyor belt for further processing. The imaging device is communicatively
coupled with an image acquisition system which processes the captured images
using image processing algorithms to obtain the size distribution of the green
pellets lying on the conveyor belt. The size distribution is shown on display. The
size distribution curve is used in decision making regarding operation of the green
pellets in the induration furnace or pellet plant.
[0015] In another implementation, the camera device for capturing images at high
temperature and dusty environment is covered in a double jacketed camera
enclosure. Further, the imaging device has an air inlet for allowing compressed air
inside the double jacketed camera enclosure and a plurality of air purging outlets
are placed in front of the double jacketed camera enclosure. Further, the plurality
of air purging outlet allows the compressed air to come out from the double
jacketed camera enclosure from front side which is facing conveyor belt.

[0016] In order to further understand the characteristics and technical contents of
the present subject matter, a description relating thereto will be made with
reference to the accompanying drawings. However, the drawings are illustrative
only but not used to limit scope of the present subject matter.
BRIEF DESCRIPTION OF THE DRAWINGS
[0017] It is to be noted, however, that the appended drawings illustrate only
typical embodiments of the present subject matter and are therefore not to be
considered for limiting of its scope, for the invention may admit to other equally
effective embodiments. The detailed description is described with reference to the
accompanying figures. In the figures, a reference number identifies the figure in
which the reference number first appears. The same numbers are used throughout
the figures to reference like features and components. Some embodiments of
system or methods or structure in accordance with embodiments of the present
subject matter are now described, by way of example, and with reference to the
accompanying figures, in which:
[0018] Fig. 1 illustrates system implementation having camera, illumination light,
conveyor belt along with green balls, in accordance with an embodiment of the
present subject matter;
[0019] Fig. 2 illustrates structure of double jacketed enclosure of the camera, in
accordance with an embodiment of the present subject matter;
[0020] Fig. 3 illustrate schematic block diagram of complete system for
processing of the image, in accordance with an embodiment of the present subject
matter;
[0021] Fig. 4 illustrates block diagram of the image acquisition system, in
accordance with an embodiment of the present subject matter;
[0022] Fig. 5 illustrates a method for image processing of the green balls for size
characterization of the green balls for feeding in induration furnace, in accordance
with an embodiment of the present subject matter;

[0023] Fig. 6 illustrates process images for size characterization of the green balls,
in accordance with an embodiment of the present subject matter;
[0024] Fig. 7 illustrates size distribution and Gaussian curve fitting for
identification of mean and standard deviation based on the calculated diameter, in
accordance with an embodiment of the present subject matter; and
[0025] Fig. 8 illustrates plant installation for the present subject, in accordance
with an embodiment of the present subject matter.
[0026] The figures depict embodiments of the present subject matter for the
purposes of illustration only. A person skilled in the art will easily recognize from
the following description that alternative embodiments of the structures and
methods illustrated herein may be employed without departing from the principles
of the disclosure described herein.
DESCRIPTION OF THE PREFERRED EMBODIMENTS:
[0027] The subject matter disclosed herein relates to a method and system for
automatic size characterization of green balls being fed into an induration furnace
using image processing techniques. The system comprises an imaging and
illumination device installed above conveyor belt in the pellet plant. The imaging
device takes the images of green pellets lying on the conveyor belt for further
processing. The imaging device is communicatively coupled with an image
acquisition system which processes the obtained images using image processing
algorithms to obtain the size distribution of the green pellets lying on the
conveyor belt. The size distribution is shown on display. The size distribution is
used in decision making regarding operation of the green pellets in the induration
furnace or pellet plant.
[0028] As explained above in the problem in prior art section, the distribution of
particle sizes in a sample can be determined by individually passing each particle
in the sample, or a portion of the sample, through the scattered light detection
apparatus, and tabulating the sizes of the various particles. In this practice,
conventional method is generally restricted to particles larger than 0.5 microns.

Moreover, the conventional method is relatively slow and inefficient, because
particles must be presented and detected individually in the apparatus. Therefore,
conventional techniques for determining the size and characterization of the size
of the green balls are slow, ineffective, based on the angular dependence of the
scattered light intensity, and determine the size of individual particle.
[0029] According to an implementation of the present subject matter, a system
includes imaging and illumination system to capture image of green balls lying on
the surface of conveyor belt of the induration furnace. The present system further
includes an image acquisition system to process the captured image and provide
the processed data to the server for storage and displaying the same on the display.
Based on the processed data, the pellet plant specifically induration furnace can be
operated and control in more efficient manner to produce high quality pellets.
[0030] In one embodiment of the present subject matter, the image acquisition
system comprises an image processing module which receives the captured image
of the plurality of green balls lying on conveyor belt of the induration furnace
from the imaging device, i.e., camera or CCD camera. The image acquisition
system is calibrated based on the checker board so as to associate the pixel values
of the image to the values in terms of millimeters. After processing the image, the
image processing module saves the data in the image processed data. Further, the
image processing module calculates the diameter of the green balls and generates
a curve based on the size characterization of the diameters of the green balls.
[0031] In another embodiment of the present subject matter, the camera of the
system is protected in a double jacket. The present camera device and lighting
device assembly has a compressed air purging unit with pressure of about 5 bar to
protect the camera device and the lighting device from the dust and the heat of the
system. Further, the compressed air inside the camera device also cools the
camera device and the lighting device assembly and purging the face of the
camera and light device assembly for better imaging and illumination capabilities.
[0032] It should be noted that the description and figures merely illustrate the
principles of the present subject matter. It should be appreciated by those skilled

in the art that conception and specific embodiment disclosed may be readily
utilized as a basis for modifying or designing other structures for carrying out the
same purposes of the present subject matter. It should also be appreciated by those
skilled in the art that by devising various arrangements that, although not
explicitly described or shown herein, embody the principles of the present subject
matter and are included within its spirit and scope. Furthermore, all examples
recited herein are principally intended expressly to be for pedagogical purposes to
aid the reader in understanding the principles of the present subject matter and the
concepts contributed by the inventor(s) to furthering the art, and are to be
construed as being without limitation to such specifically recited examples and
conditions. The novel features which are believed to be characteristic of the
present subject matter, both as to its organization and method of operation,
together with further objects and advantages will be better understood from the
following description when considered in connection with the accompanying
figures.
[0033] These and other advantages of the present subject matter would be
described in greater detail with reference to the following figures. It should be
noted that the description merely illustrates the principles of the present subject
matter. It will thus be appreciated that those skilled in the art will be able to devise
various arrangements that, although not explicitly described herein, embody the
principles of the present subject matter and are included within its scope.
[0034] Fig. 1 illustrates system implementation having camera, illumination light,
conveyor belt along with green balls, in accordance with an embodiment of the
present subject matter. The present system comprises an imaging device, i.e.,
camera device 102, a lighting device 101, a plurality of green balls 104, and a
conveyor belt 105. Where the plurality of green balls 104 are lying on the
conveyor belt 105 of induration furnace. The camera device 102, such as CCD
camera is installed over the conveyor belt 105 along with the lighting device 101.
The lighting device 101, such as halogen lights are installed above the camera
device 102. The lighting devices 101 have very high illumination capacity so that

the camera device 102 can capture images with better resolution quality even in
dusty environments. Further, field view 103 of the camera device 102 is based on
the width of the conveyor belt 105 on which the plurality of green balls 104 are
being transported. The illumination levels of the lighting device 101 are selected
based on the amount of the dust prevalent at the location, i.e., over the conveyor
belt 105. Accordingly, higher the dust level, higher the illumination is required to
negate the effect of the dust. When illumination level and field view of the camera
device 102 is selected, the camera device 102 captures the images of the plurality
of green balls lying on the surface of the conveyor belt 105 and send the captured
image to the image acquisition system.
[0035] Fig. 2 illustrates structure of double jacketed enclosure of the camera
device 102, in accordance with an embodiment of the present subject matter. The
camera device 102 includes air inlet 201, double jacketed camera enclosure 202
(interchangeably can be referred as enclosure 202), air purging outlet 203, and
camera housing 204. The double jacketed camera enclosure 202 encloses the
camera housing 204. The double jacketed camera enclosure has two jackets, i.e.,
outer jacket and inner jacket. Where the outer jacket is in contact with the
environment and inner jacket is in contact with the camera device 102. Between
the outer jacket and the inner jacket compressed air circulates to cool the inner
jacket encloses the camera device 102. The double jacketed camera enclosure has
the air inlet 201 from where compressed air inserts in the enclosure and circulates
in the enclosure between the outer jacket and the inner jacket.
[0036] In the double jacketed camera enclosure 202 has plurality of air purging
outlets 203 which are present at the end of the double jacketed camera enclosure
202 which faces the conveyor belt 105. The compressed air circulates in the
enclosure 202 between the inner jacket and the outer jacket and then circulated
compressed air comes out from the front of the double jacketed camera enclosure
202 from the plurality of air purging outlets 203 in such a way that the
compressed air purges the camera device glass in the front of the double jacketed
camera enclosure 202. In this way the compressed air keeps the front face of the

camera device 102 clean even in the dusty environment. Where the pressure of the
compressed air inside the enclosure is about 5 bar. The compressed air inside the
enclosure 202 also cools the camera device and the lighting assembly of the
system in high working temperature. Accordingly it increases the efficiency,
quality, and life time of the camera device 102.
[0037] Fig. 3 illustrates schematic block diagram of complete system for
processing of the image, in accordance with an embodiment of the present subject
matter. The present block diagram explains the methodology of size
characterization of the green balls. Once the image of the green balls 103 (sinter
particles) is captured by the camera device 102, it is sent to image acquisition
system for further processing. The image acquisition system process the captured
imaged using image processing algorithm, i.e., checker board and canny edge
detection algorithm. The image acquisition system calculates the diameter of the
plurality of green balls from the number of pixel in the image. Based on calculated
diameter of the plurality of green balls, a normal distribution curve with the mean
and standard deviation of the sizes is generated and send to the server for storage
and display.
[0038] Fig. 4 illustrates block diagram of the image acquisition system, in
accordance with an embodiment of the present subject matter. The present image
acquisition system 300 includes one or more processor(s) 301, interface(s) 302,
memory 303 coupled to the processor, modules 304, and data 307. The
processor(s) 301, may be implemented as one or more microprocessors,
microcomputers, microcontrollers, digital signal processors, central processing
units, logic circuitries, and/or any devices manipulate signals based 5 on
operational instructions. Among other capabilities, the processor(s) 301 is
configured to fetch and execute computer-readable instructions stored in the
memory 303. Further processor 301 is a hardware device which communicates
with the other software and hardware and processes the data and provides the
results.

[0039] The interface(s) 302 may include a variety of software and hardware
interfaces, for example, interfaces for peripheral device(s), such as a keyboard, a
mouse, an external memory, and display device. Further, the interfaces 302 may
facilitate multiple communications within a wide variety of protocol types
including, operating system to application communication, inter process
communication, client server communication, etc.
[0040] The memory 206 can include any computer-readable medium known in
the art including, for example, volatile memory, such as static random access
memory (SRAM) and dynamic random access memory (DRAM), and/or non-
volatile memory, such as read only memory (ROM), erasable programmable
ROM, flash memories, hard disks, optical disks, and magnetic tapes.
[0041] Further modules 304 and data 307 may be coupled with the processor(s)
301. The modules 304, amongst other things, include routines, programs, objects,
components, data structures, etc., which perform particular tasks or implement
particular abstract data types. The modules 304 may also be implemented as,
signal processor(s), state machine(s), logic circuitries, and/or any other device or
component that manipulate signals based on operational instructions. In another
aspect of the present subject matter, the modules 304 may be computer-readable
instructions which, when executed by a processor/processing unit, perform any of
the described functionalities. The machine-readable instructions may be stored on
an electronic memory device, hard disk, optical disk or other machine-readable
storage medium or non-transitory medium.
[0042] In an implementation, module(s) 304 include image processing module
305 and other module(s) 306. The other module(s) 306 may include programs or
coded instructions that supplement applications or functions performed by the
system 300. The data 307 includes Image process data 308 and other data 309.
The other data 309 amongst other things, may serve as a repository for storing
data that is processed, received, or generated as a result of the execution of one or
more modules in the module(s) 304. Although the data 307 is shown internal to
the system 307, it may be understood that the data 307 can reside in an external

repository, such as server 310, which may be coupled to the system 300. The
system 300 may communicate with the external repository through the interface(s)
302 to obtain information from the data 307.
[0043] As explained above, the image acquisition system 300 calculates the
diameter of the plurality of green balls and does the size characterization of the
same. In one implementation, the image processing module 305 receives the
captured image from the camera device 102. The image processing module 305
enhances and processes the received image using filters, such as top hat filter and
morphological operators. Further, the processed images are saved in the image
process data 308 in the system 300 for further processing. The image processing
module 305 segregates and separates the plurality of green balls using canny edge
detection algorithm. The canny edge detection algorithm uses a multi-
stage algorithm to detect a wide range of edges in images. Once the plurality of
green balls are separated in the processed image, the image processing module
305 further process the processed images using series of morphological operators,
such as Bridging, Dilation, Top hat filters, Image subtraction in an iterative
manner in such a way that no two green balls are characterized more than once.
[0044] Further the image processing module 305 process the processed image
save in the image processed data 308 and calculates the diameter of each green
ball of the plurality of green balls based on the number of pixels in the processed
image. The image processing module 305 saves the processed image data and
diameter in the image process data 308. Further, the image processing module 305
sends the calculated diameter of each green ball to the server and display device to
display the data in the distribution curve.
[0045] Fig. 5 illustrates a method for size characterization of the plurality of green
ball, in accordance with an embodiment of the present subject matter. Present
methodology is not only limited to the described steps and combination of the
steps. A person skilled in the art will understand the steps of the method and can
modify the steps and achieve the end results.

[0046] The method may be described in the general context of computer
executable instructions. Generally, computer executable instructions can include
routines, programs, objects, components, data structures, procedures, modules,
functions, etc., that perform particular functions or implement particular abstract
data types. The method may also be practiced in a distributed computing
environment where functions are performed by remote processing devices that are
linked through a communications network. In a distributed computing
environment, computer executable instructions may be located in both local and
remote computer storage media, including memory storage devices.
[0047] At block 502, camera device of the image acquisition system is calibrated
based on the checker board. The image acquisition system is calibrated to
associate the pixel values of the image to the values in terms of millimeters. From
the camera calibration, position of the image center in the image, focal length,
different scaling factors for rows and column pixels, skew factor, and lens
distortion can be affected.
[0048] At block 504, the plurality of green balls is separated and segregated using
canny edge detection algorithm. The canny edge detection algorithm uses a multi-
stage algorithm to detect a wide range of edges in images. Based on the detected
edges in the image, plurality of green balls can be separated and segregated.
[0049] At block 506, the processed images using series of morphological
operators, such as Bridging, Dilation, Top hat filters, Image subtraction in an
iterative manner in such a way that no two green balls are characterized more than
once. The image processing module 305 does this processing and save the process
data in the image process data 308.
[0050] At block 508, diameter of each separated green ball is calculated from the
number of pixels in the separated green ball image in the processed image. The
image processing module 305 counts the number of pixels in the image for each
separated ball and convert the number of pixels in the millimeter to obtain the
diameter of each green ball. The image processing modules sends the calculated
data the image process data 308 and server for further processing of the data.

[0051] At block 510, calculated data is accumulated in the image process data 308
and a normal distribution curve with mean and standard deviation of calculated
sizes is generated. The generated curve is sent to the display device of the operator
of the pellet plant. Based on the visual data, the operator controls the pellet plant
at the induration furnace in a more efficient manner.
[0052] Fig. 6 illustrates the sequence of processed images stage wise. Fig. 6 (a)
illustrates the original image captured by the camera device 102. Fig. 6 (b)
illustrates the filtered image of the original image. The original image is filtered
by the image processing module 305 using several morphological filters, such as
bridging, dilation, top hat filters, and image subtraction. Fig. 6 (c) illustrates the
processed image by canny edge detection algorithm. By processing the image
with the canny edge detection algorithm, each particle is clearly visible in the
image with sharp edge. Based on the clear particle identification, the image
processing module 305 calculates the diameter of each particle from the number
of pixels in the each particle.
[0053] Fig. 7 illustrates a graph of the isolated green balls which indicate the size
of each green ball. The isolated green balls in which the borders are distinctive are
identified and sizes are recorded.
[0054] Fig. 8 illustrates the installation of the system.
Advantages of the Invention over prior art:
[0055] The system is online characterization by means of which it provides data
once every 20 seconds. The prior arts are lab analysis which normally takes an
hour or two before the results are provided.
[0056] Since the present subject matter is online measurement, future control of
the process can also be automated in real time based on this data. This would
provide more accurate process control to provide optimal sized pellets to the blast
furnaces.

[0057] The present subject matter provides results on the web, by means of which
everyone in the plant can access the data at any point of time irrespective of their
locations. This provides real time process visualization.
[0058] The present method of image processing to the green balls being fed into
the induration furnace proves to be very robust in terms of the environmental
conditions present and also proving to be a continuous measurement system rather
than the sampling system which was the major disadvantage with prior art
involving scattering of light. Image processing algorithms are also very robust
thereby making the complete system accurate and efficient.
[0059] Although implementations for the method and the system for size
characterization of the plurality of green balls based by image acquisition system
have been described in language specific to structural features and/or method, it is
to be understood that the present subject matter is not necessarily limited to the
specific features described. Rather, the specific features and methods are disclosed
as embodiments for the present subject matter. Numerous modifications and
adaptations of the system/device/structure of the present invention will be
apparent to those skilled in the art, and thus it is intended by the appended claims
to cover all such modifications and adaptations which fall within the scope of the
present subject matter.


We claim:
1. A system for size characterization of a plurality of green balls (104), the
system comprises:
a lighting device (101);
a imaging device (102) is placed below the lighting device (101);
the plurality of green balls lying on surface of conveyor belt (105),
wherein the imaging device (102) captures image of the plurality of green balls
(104).
2. The system as claimed in claim 1, wherein the lighting system (101)
comprises halogen lights with very high illumination capacity.
3. The system as claimed in claim 1, wherein field view of lens of the
imaging device (102) is selected based on the width of the conveyor belt (105).
4. An imaging device (102) for capturing images at high temperature and
dusty environment, the imaging device comprises:
a double jacketed camera enclosure (202) encloses a camera device
(204);
an air inlet (201) for allowing compressed air inside the double
jacketed camera enclosure (202); and
a plurality of air purging outlet (203) are placed in front of the double
jacketed camera enclosure (202), wherein the plurality of air purging allows
the compressed air to come out from the double jacketed camera enclosure
(202) from front side which is facing conveyor belt (105).
5. The imaging device (102) as claimed in in claim 4, wherein the double
jacketed camera enclosure (202) has two parts outer jacket and inner jacket.

6. An image acquisition system (300) for size characterization of plurality of
green balls (104) in pellet plant, the image acquisition system (300) comprises:
a processor (301) coupled with the memory (303);
an image processing module (305) coupled with the processor
(301) to process captured images of the plurality of green balls (104),
wherein the image processing module (305) coupled with the processor to,
segregates and separate each green ball in the plurality of
green balls using canny edge detection algorithm;
processes the captured image using morphological
operators to remove noise;
calculates diameter of each green ball of the plurality of
green balls (104) from the processed image based on number of
pixel;
generates a normal distribution curve with the mean and
standard deviations of the calculated diameters; and
sends the generated normal distribution curve to server for
displaying and monitoring of the pellet plant.
7. The image acquisition system (300) as claimed in claim 6, wherein the
image processing module (305) identify each green ball in the captured image
clearly by using the canny edge detection algorithm.
8. The image acquisition system (300) as claimed in claim 6, wherein the
image acquisition system (300) is calibrated based on a checker board.
9. The image acquisition system (300) as claimed in claim 6, wherein the
image acquisition module (305) converts the number of pixels of the image into
millimeter for the diameter.
10. A computer implemented method for size characterization of plurality of
green balls (104) in induration furnace, the method comprising:
calibrating camera based on the checker board;
receiving, by a processor (301), a captured image from the camera
via network;

segregating and separating, by the processor (301), the plurality of

green balls (104) in the image using canny edge detection algorithm;
processing, by the processor (301), tile image using morphological
operators;
calculating, by the processor (301), diameter of each seprated green
ball of the plurality of green balls (104) from the processed image based

on number of pixel; and
generating, by the processor (301), a normal distribution curve

with mean and standard deviations based on the calculated diameter of the
each green ball.