MATEC Web Conf.
Volume 336, 20212020 2nd International Conference on Computer Science Communication and Network Security (CSCNS2020)
|Number of page(s)||6|
|Section||Intelligence Algorithms and Application|
|Published online||15 February 2021|
A minimum cross-entropy multi-thresholds segmentation algorithm based on improved WOA
1 Shanghai Dianji University, Shanghai, China
* Corresponding author: firstname.lastname@example.org
Minimum cross-entropy is widely used in image segmentation for its effectiveness. However, when the algorithm is applied to multi-threshold segmentation, there are some problems such as large amount of calculation, time-consuming and poor practicability due to exhaustive search for the optimal threshold. Therefore, in this paper, a hybrid whale optimization algorithm (IWOA) which incorporates whale optimization algorithm (WOA) and invasive weed optimization (IWO) is proposed and the minimum cross-entropy is used as the fitness function of optimization algorithm to select the optimal threshold. It is established that IWOA algorithm is able to select the optimal threshold in more accuracy and segment high quality image than other algorithms.
© The Authors, published by EDP Sciences, 2021
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.