Image segmentation with a multilevel threshold using backtracking search optimization algorithm

  • Hather Ibraheem Abed

Abstract

Image segmentation is an important process in image processing. Though, there are many applications are affected by the segmentation methods and algorithms, unfortunately, not one technique, but the threshold is the popular one. Threshold technique can be categorized into two ways either simple threshold which has one threshold or multi- thresholds separated which has more than two thresholds . In this paper, image segmentation is used simple threshold method which is a simple and effective technique. Therefore, to calculate the value of threshold solution which is led to increase exponentially threshold that gives multi-thresholds image segmentation present a huge challenge. This paper is considered the multi-thresholds segmentation model for the optimization problem in order to overcome the problem of excessive calculation. The objective of this paper proposed an slgorithmto solve the optimization problem and realize multi-thresholds image segmentation. The proposed multi-thresholds segmentation algorithm should be segmented  the raw  image into pieces, and compared with other algorithms results. The experimental results that show multi-thresholds image segmentation based on backtracking search optimization algorithm are feasible and have a good segmentation.


 


http://dx.doi.org/10.25130/tjps.25.2020.036

Published
Mar 17, 2020
How to Cite
ABED, Hather Ibraheem. Image segmentation with a multilevel threshold using backtracking search optimization algorithm. Tikrit Journal of Pure Science, [S.l.], v. 25, n. 2, p. 102-109, mar. 2020. ISSN 2415-1726. Available at: <http://tjps.tu.edu.iq/index.php/j/article/view/964>. Date accessed: 02 apr. 2020. doi: http://dx.doi.org/10.25130/j.v25i2.964.
Section
Articles