MULTILEVEL IMAGE THRESHOLDING USING ARTIFICIAL INTELLIGENCE TECHNIQUES.

  • Department of Electronics and Instrumentation Engineering, St. Joseph?s College of Engineering, Chennai-600119.
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Analysis and comparison of various multilevel segmentation techniques to efficiently detect the tumourous region from MR Brain Images in early stages.To extract the abnormal tissues using multilevel image thresholding based on PSO. In the area of image processing, segmentation of an image into multiple regions is very important for classification and recognition steps. In this project we describe a novel method for segmentation of images based on Particle Swarm optimization for determining multilevel threshold for a given image. The proposed method is compared with other known multilevel segmentation methods to demonstrate its efficiency.

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[R.Sabeena and C.Subassree. (2017); MULTILEVEL IMAGE THRESHOLDING USING ARTIFICIAL INTELLIGENCE TECHNIQUES. Int. J. of Adv. Res. 5 (May). 94-100] (ISSN 2320-5407). www.journalijar.com

R.SABEENA,C.SUBASSREE
Anna University

DOI:

Article DOI: 10.21474/IJAR01/4083      
DOI URL: https://dx.doi.org/10.21474/IJAR01/4083

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