Improved thresholding based on negative selection algorithm (NSA)

Mahapatra, Prasant Kumar; Kaur, Mandeep; Sethi, Spardha; Thareja, Rishabh; Kumar, Amod; Devi, Swapna

Affiliations

¹V-2 (Biomedical Instrumentation Division), CSIR-Central Scientific Instruments Organisation, Sector-30, Chandigarh, 160030, India

²University Institute of Engineering and Technology, Punjab University, Chandigarh, India

³Department of Electronics and Communication, National Institute of Technical Teachers’ Training and Research, Sector-26, Chandigarh, 160026, India

Abstract and keywords

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.

Keywords: Thresholding; Image segmentation; Negative selection algorithm; Artificial immune system; Maximum information entropy

Links

DOI: 10.1007/s12065-013-0089-8

History

Received: 2013-04-18

Revised: 2013-08-30

Accepted: 2013-08-31

Online: 2013-09-01

Cited Works (4)

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