Segmentation using Outlier Based Adaptive Thresholding
Vishal B. Langote1, D. S. Chaudhari2
1Vishal B. Langote, Department of Electronics and Telecommunication, Amravati University, GCOE, Amravati (Maharashtra), India.
2Dr. Devendra S. Chaudhari, Department of Electronics and Telecommunication, PhD. Indian Institute of Technology, Bombay, Mumbai (M.H), India.
Manuscript received on 18 June 2012 | Revised Manuscript received on 25 June 2012 | Manuscript published on 30 June 2012 | PP: 164-167 | Volume-1 Issue-2, June 2012 | Retrieval Number: B0224051212/2012©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 plays an important role in image analysis as a frequent pre-processing step, which divides the image into set of different segments. Thresholding is an easy yet efficient method for image segmentation, while dividing different objects with distinct gray levels. Finding an effective threshold is especially complicated task in the segmentation. In this paper, for efficient threshold selection fuzzy methodology used which produces better segmentation results than other methodologies. It was observed that at different background intensity levels favourable results were obtained.
Keywords: Image Segmentation, thresholding, fuzzy methodology
Scope of the Article: Image Security