Objective Evaluation Parameters of Image Segmentation Algorithms
Manisha Sharma1, Vandana Chouhan2
1Manisha Sharma, Electronics and Telecommunication, B.I.T, Durg, (C.G), India.
2Vandana Chouhan, Electronics and Telecommunication, MMCT, Raipur, (C.G), India.
Manuscript received on November 21, 2012. | Revised Manuscript received on December 03, 2012. | Manuscript published on December 30, 2012. | PP: 84-87 | Volume-2, Issue-2, December 2012.  | Retrieval Number: B0814112212 /2012©BEIESP

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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: Image segmentation is the process of partitioning an image into multiple segments, so as to change the representation of an image into something that is more meaningful and easier to analyze. Several general-purpose algorithms and techniques have been developed for image segmentation. However ,evaluation of segmentation algorithms thus far has been largely subjective , leaving a system designer to judge the effectiveness of a technique based only on intuition and results in the form of few example segmented images .This is largely due to image segmentation being a ill defined problem-there is no unique ground truth segmentation of an image against which the output of an algorithm may be compared .There is a need for researchers to know on what parameters there suggested techniques can be evaluated .In this paper we have surveyed 100 papers to present various evaluation parameters. This paper presents 13 performance evaluation parameters that can be used to perform a quantitative comparison between image segmentation.
Keywords: Segmentation, MRI,