A novel laser spot detection method based on secretary bird optimization algorithm

In recent years, the development of laser technology has enabled numerous applications. Detecting laser spots within optical image is crucial for high-precision tasks, which remain challenges due to background noise and grayscale similarity. Traditional threshold-based optical image segmentation methods can offer simplicity and efficiency for low-contrast images, but the segmentation quality is highly relative to the threshold selection. To address the above challenges, a novel swarm intelligence algorithm named Secretary Bird Optimization Algorithm (SBOA) is introduced to select the optimal threshold. Experimental results proved the effectiveness of the proposed method. This work conducted a comparative experiment with a constant maximum iteration number and a changing population size. Comparison with the traversal method and the Particle Swarm Optimization (PSO) method demonstrated superior detection accuracy and efficiency of the SBOA method. The proposed method has higher precision and less convergence times than the PSO method and faster execution time than the traversal method with a population size of 10 or less.