Technical gazette, Vol. 32 No. 2, 2025.
Original scientific paper
https://doi.org/10.17559/TV-20240302001362
Infrared Image Segmentation Method Based on Variable Helix Optimized-Sparrow Search Algorithm
Jilan Huang
; Geely University of China, 641423, ChengDu, China
*
Xing Yang
; Geely University of China, 641423, ChengDu, China
Zhixiong Jin
; Geely University of China, 641423, ChengDu, China
* Corresponding author.
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.
Keywords
division; image; otsu; sparrow search algorithm; threshold; variable helix
Hrčak ID:
328640
URI
Publication date:
27.2.2025.
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