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.2018.088424

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

Received: 13 Oct 2016
Accepted: 09 Jan 2017
Published online: 07 Dec 2017 *

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