Infrared Image Segmentation Method Based on Variable Helix Optimized-Sparrow Search Algorithm
Year: 2025
Type: article
Abstract: This study proposes an infrared image segmentation method based on a Variable Helix Optimized-Sparrow Search Algorithm (VHO-SSA) to address the limitations of traditional image segmentation algorithms.The proposed method combines the Otsu threshold algorithm with an optimized sparrow search algorithm, which utilizes a variable helix position search method and a best point set method.The performance of the proposed method is evaluated using several benchmark functions and compared with other state-of-the-art algorithms.The results demonstrate that the VHO-SSA achieves high segmentation accuracy (up to 0.98) and maintains a high structural similarity index (above 0.90) in the presence of noise.The proposed method shows promise for improving the segmentation of infrared images in various applications.
Authors: Huang, Jilan, Yang, Xing, Jin, Zhixiong
Institution: Geely University of China
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $431
OpenAlex ID: W4408046767