Comparison between Otsu’s Image Thresholding Technique and Iterative Triclass

  IJCTT-book-cover
 
International Journal of Computer Trends and Technology (IJCTT)          
 
© 2016 by IJCTT Journal
Volume-33 Number-2
Year of Publication : 2016
Authors : Prof.Sushilkumar N. Holambe, Priyanka G. Kumbhar
  10.14445/22312803/IJCTT-V33P117

MLA

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.