Comparison between Otsu’s Image Thresholding Technique and Iterative Triclass
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International Journal of Computer Trends and Technology (IJCTT) | 
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| © 2016 by IJCTT Journal | ||
| Volume-33 Number-2 |
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| Year of Publication : 2016 | ||
| Authors : Prof.Sushilkumar N. Holambe, Priyanka G. Kumbhar | ||
| DOI : 10.14445/22312803/IJCTT-V33P117 |
Prof.Sushilkumar N. Holambe, Priyanka G. Kumbhar "Comparison between Otsu’s Image Thresholding Technique and Iterative Triclass". International Journal of Computer Trends and Technology (IJCTT) V33(2):80-82, March 2016. ISSN:2231-2803. www.ijcttjournal.org. Published by Seventh Sense Research Group.
Abstract -
Medical image segmentation is
related to the segmentation of known anatomic
structures from medical images. Structures consists
of organs or parts such as cardiac ventricles or
kidneys, abnormalities such as tumors and cysts, as
well as other structures such as vessels, brain
structures etc. The complete objective of this
segmentation is known as computer-aided diagnosis
which is used by doctors in evaluating medical
images or in recognizing abnormalities in a medical
image.
Segmentation means the process of
partitioning a digital image into multiple regions
(sets of pixels). The methods of segmentation is used
to simplify and change the representation of an
image into something that is more meaningful and
easy to understand. The result of image
segmentation is a set of regions that combine the
whole image, or a set of contours extracted from the
image. Each of the pixels in a region is same with
respect to some characteristic or computed things,
such as color, concentration, or texture. Adjacent
regions are not similar with each other they differs
in some characteristics. A rugged segmentation
procedure brings the process a long way towards
successful solution of an image difficulty. Outcome
of the segmentation stage is raw pixel data,
consisting of both the boundary of a region and all
the points in the region.
In this paper, we compared two methods of
image segmentation OTSU’s method and new
iterative triclass thresholding technique of image
segmentation.
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Keywords
Segmentation, binary, thresholding.