Open AccessOtsu Image Threshold Segmentation Method Based on Seagull Optimization Algorithm
Author(s) -
Yuyin Wang
Publication year - 2020
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1650/3/032181
Subject(s) - otsu's method , image segmentation , segmentation , artificial intelligence , image (mathematics) , computer science , region growing , algorithm , scale space segmentation , computer vision , pattern recognition (psychology)
In this paper, a two-dimensional Otsu image threshold segmentation method based on Seagull optimization is proposed. The Seagull algorithm is used to calculate the threshold points of two-dimensional Otsu image segmentation and segment the image. The algorithm makes full use of the seagull migration operator of global search and the seagull attack operator of simulated local search. Simulation results show that the algorithm not only improves the speed, but also improves the segmentation accuracy.