"基于MATLAB的图像分割算法研究与应用效果分析"

The research presented in this article focuses on the study of image segmentation algorithms based on MATLAB. The paper provides an analysis of various classic image segmentation techniques, including edge detection, threshold segmentation, and region-growing. In terms of edge detection algorithms, the Roberts operator, Sobel operator, Prewitt operator, Laplacian operator, LoG (Laplacian-Gauss) operator, and Canny operator are compared in terms of segmentation steps, methods, and criteria. It is observed that the edge detection results obtained using the Canny operator, considering its three criteria, are the most satisfactory. The key aspect of threshold segmentation techniques lies in determining the appropriate threshold value. Only when the threshold value is accurately determined can effective separation of objects and background be achieved. However, this method only yields significant segmentation results for images with distinct grayscale distributions and significant differences between the objects and the background. Furthermore, the article introduces the basic idea of region growing, which involves grouping together pixels with similar properties to form new regions. The study also analyzes the future research directions in image segmentation technology. In conclusion, this article provides a comprehensive analysis of various image segmentation techniques, highlighting their principles and application effects. It emphasizes the importance of selecting the suitable algorithm based on the characteristics of the image and the desired segmentation results. The findings of this research can serve as a valuable reference for researchers and practitioners in the field of image processing and analysis. Keywords: image processing, image segmentation.