CFP last date
20 December 2024
Reseach Article

Using Flower Pollination Algorithm for Segmentation with Threesholding

by Ibrahim M. El-Henawy, Mohamed A. Fahmy
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 181 - Number 28
Year of Publication: 2018
Authors: Ibrahim M. El-Henawy, Mohamed A. Fahmy
10.5120/ijca2018918135

Ibrahim M. El-Henawy, Mohamed A. Fahmy . Using Flower Pollination Algorithm for Segmentation with Threesholding. International Journal of Computer Applications. 181, 28 ( Nov 2018), 36-41. DOI=10.5120/ijca2018918135

@article{ 10.5120/ijca2018918135,
author = { Ibrahim M. El-Henawy, Mohamed A. Fahmy },
title = { Using Flower Pollination Algorithm for Segmentation with Threesholding },
journal = { International Journal of Computer Applications },
issue_date = { Nov 2018 },
volume = { 181 },
number = { 28 },
month = { Nov },
year = { 2018 },
issn = { 0975-8887 },
pages = { 36-41 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume181/number28/30119-2018918135/ },
doi = { 10.5120/ijca2018918135 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T01:07:34.745831+05:30
%A Ibrahim M. El-Henawy
%A Mohamed A. Fahmy
%T Using Flower Pollination Algorithm for Segmentation with Threesholding
%J International Journal of Computer Applications
%@ 0975-8887
%V 181
%N 28
%P 36-41
%D 2018
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The bio-inspired algorithm was development to generate optimum threshold values for image segmentation the flower pollination algorithm (FPA) is one of heuristic and bio-inspired algorithms that deals with continuous and combinatorial optimization problems and it can use for image segmentation of the image satellite. The satellite images are very hard to be segmented because the images are weakly correlated and the important regions are unclear. The purpose of the research is to use “FPA” in satellite image segmentation.

References
  1. Cheng, H.-D., et al., Color image segmentation: advances and prospects. Pattern recognition, 2001. 34(12): p. 2259-2281
  2. Romshoo, S.A. and I. Rashid, Assessing the impacts of changing land cover and climate on Hokersar wetland in Indian Himalayas. Arabian Journal of Geosciences, 2014. 7(1): p. 143-160.
  3. Yang, X.-S., Nature-inspired metaheuristic algorithms. 2010: Luniver press.
  4. Yang, X.-S. Flower pollination algorithm for global optimization. in International conference on unconventional computing and natural computation. 2012. Springer
  5. Davies, E., Stable bi-level and multi-level thresholding of images using a new global transformation. IET Computer vision, 2008. 2(2): p. 60-74.
  6. Arora, S., et al., Multilevel thresholding for image segmentation through a fast statistical recursive algorithm. Pattern Recognition Letters, 2008. 29(2): p. 119-125.
  7. Kapur, J.N., P.K. Sahoo, and A.K. Wong, A new method for gray-level picture thresholding using the entropy of the histogram. Computer vision, graphics, and image processing, 1985. 29(3): p. 273-285.
  8. Nigdeli, S.M., G. Bekdaş, and X.-S. Yang, Application of the flower pollination algorithm in structural engineering, in Metaheuristics and optimization in civil engineering. 2016, Springer. p. 25-42.
  9. Yang, X.-S. and S. Deb. Cuckoo search via Lévy flights. in Nature & Biologically Inspired Computing, 2009. NaBIC 2009. World Congress on. 2009. IEEE.
  10. Lim, W.C.E., G. Kanagaraj, and S. Ponnambalam, PCB drill path optimization by combinatorial cuckoo search algorithm. The Scientific World Journal, 2014. 2014.
  11. Suresh, S. and S. Lal, An efficient cuckoo search algorithm based multilevel thresholding for segmentation of satellite images using different objective functions. Expert Systems with Applications, 2016. 58: p. 184-209.
Index Terms

Computer Science
Information Sciences

Keywords

Flower pollination segmentation threesholding Kapur’s entropy