CV Segmentation Model Code Implementation

This code implements computer vision segmentation for three distinct images. Image segmentation is the process of partitioning digital images into multiple segments or regions to facilitate better understanding of image contents. The implementation allows side-by-side comparison of segmentation results across different images, providing insights into the strengths and limitations of the segmentation algorithm. The code structure includes preprocessing modules for image normalization, core segmentation algorithms using region-based or edge detection approaches, and post-processing components for result refinement. Furthermore, the code serves as a flexible framework for parameter tuning and algorithm enhancement to achieve improved segmentation accuracy. Key functions include image I/O handling, segmentation metric calculation, and visualization tools for result comparison. Overall, this implementation provides valuable reference material and practical tools for researchers studying image segmentation techniques.