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01.02.2014 | Research Paper

Improved thresholding based on negative selection algorithm (NSA)

verfasst von: Prasant Kumar Mahapatra, Mandeep Kaur, Spardha Sethi, Rishabh Thareja, Amod Kumar, Swapna Devi

Erschienen in: Evolutionary Intelligence | Ausgabe 3/2014

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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.

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Titel: Improved thresholding based on negative selection algorithm (NSA)
verfasst von: Prasant Kumar Mahapatra
Mandeep Kaur
Spardha Sethi
Rishabh Thareja
Amod Kumar
Swapna Devi
Publikationsdatum: 01.02.2014
Verlag: Springer Berlin Heidelberg
Erschienen in: Evolutionary Intelligence / Ausgabe 3/2014
Print ISSN: 1864-5909
Elektronische ISSN: 1864-5917
DOI: https://doi.org/10.1007/s12065-013-0089-8

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