Int. J. of Business Intelligence and Data Mining   »   2018 Vol.13, No.1/2/3

 

 

Title: Developed global biotic cross pollination algorithm for CIS

 

Authors: K. Sasi Kala Rani; D. Rasi; S.N. Deepa

 

Addresses:
Hindusthan Institute of Technology, Othakalmandapam P.O., Coimbatore – 32, India
Hindusthan College of Engg. and Tech., Othakalmandapam P.O., Coimbatore – 32, India
Anna University Regional Centre, Sowmiyampalayam, Coimbatore – 46, India

 

Abstract: This paper focuses on the visual-based colour image segmentation with a global biotic cross pollination algorithm (GBCPA). The global biotic cross pollination algorithm segments the structurally challenging objects based on the colour, edge, entropy and edge information in the CIE L*a*b* colour space. The L*a*b* colour space is a colour-opponent space considered to approximate human vision. L* denotes the luminosity or brightness layer, chromaticity layer a* indicates colour falls along red-green axis and chromaticity layer b* indicates the blue-yellow axis. The FPO algorithm considering the global biotic cross pollination is proposed to improve the quality of the solution and computational speed. GBCPA is first introduced to find the locality of the solution. The performance of GBCPA is tested on a standard Berkeley segmentation dataset with 300 images. The dataset is illustrated under different evaluating strategies.

 

Keywords: colour image segmentation; CIS; global biotic cross pollination algorithm; GBCPA; optimisation; flower pollination algorithm; Berkeley dataset.

 

DOI: 10.1504/IJBIDM.2017.10003631

 

Int. J. of Business Intelligence and Data Mining, 2018 Vol.13, No.1/2/3, pp.108 - 128

 

Available online: 03 Nov 2017

 

 

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