  This review presents various image segmentation methods using complex
networks.
  Image segmentation is one of the important steps in image analysis as it
helps analyze and understand complex images. At first, it has been tried to
classify complex networks based on how it being used in image segmentation.
  In computer vision and image processing applications, image segmentation is
essential for analyzing complex images with irregular shapes, textures, or
overlapping boundaries. Advanced algorithms make use of machine learning,
clustering, edge detection, and region-growing techniques. Graph theory
principles combined with community detection-based methods allow for more
precise analysis and interpretation of complex images. Hybrid approaches
combine multiple techniques for comprehensive, robust segmentation, improving
results in computer vision and image processing tasks.
