"遗传算法在图像分割中的优势研究及应用"

Image segmentation is an important research topic in the field of image processing technology. It plays a crucial role in tasks such as image feature extraction and image recognition. Genetic algorithm, which simulates the biological evolution process of natural selection and genetic mechanisms, has many advantages such as robustness, parallelism, adaptability, and fast convergence. It can be applied to determine the segmentation threshold in image segmentation techniques. This study focuses on the effect of image segmentation based on genetic algorithms. Simulation experiments were conducted using Matlab software to compare the effectiveness of different image segmentation algorithms. The results show that genetic algorithm is an excellent algorithm for image segmentation, with better segmentation results compared to traditional image segmentation algorithms. Keywords: Image segmentation; Threshold calculation; Genetic algorithm; Image features. Overall, the research on image segmentation based on genetic algorithm provides valuable insights into optimizing segmentation results in image processing. It demonstrates the advantages of genetic algorithm in achieving better segmentation outcomes, showcasing its potential to enhance image processing techniques in various applications. The study sheds light on the importance of leveraging genetic algorithms in image segmentation and highlights its significance in advancing the field of image processing technology.