Improved thresholding based on negative selection algorithm (NSA)

Mahapatra, P.K. and Kaur, Mandeep and Sethi, Spardha and Thareja, Rishabh and Kumar, Amod and Devi, Swapna (2014) Improved thresholding based on negative selection algorithm (NSA). Evolutionary Intelligence, 6 (3). pp. 157-170. ISSN 1864-5909 (print version)

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Official URL: http://link.springer.com/article/10.1007%2Fs12065-...

Abstract

Thresholding is a tool of image segmentation which groups the pixels in a logical way. In this paper, a novel algorithm based on negative selection algorithm a model of artificial immune system is proposed for image thresholding. The proposed algorithm is applied on the thresholded images of lathe tool produced using maximum information entropy (MIE) and global thresholding based technique resulting in an improved image. To verify the algorithm and results, it has also been applied on some of the inbuilt MATLAB (MATrix LABoratory) images. Histogram is employed to analyze the results. Further, the results of improved algorithm are compared with the results of MIE and the global thresholding methods to check the effectiveness of the proposed method. The experimental results confirm the potential of the developed algorithm.

Item Type: Article
Uncontrolled Keywords: Thresholding; Image segmentation; Negative selection ; algorithm; Artificial immune system; Maximum information entropy
Subjects: CSIO > Computational Instrumentation
CSIO > Photonics Instrumentation
Divisions: Photonics Instrumentation
Depositing User: Ms. Jyotsana
Date Deposited: 03 May 2017 17:47
Last Modified: 03 May 2017 17:47
URI: http://csioir.csio.res.in/id/eprint/467

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