Image Segmentation by Agent-Based Pixel Homogenization

Image segmentation is the process of partitioning an image into multiple regions or objects, each representing a coherent and meaningful part image. Segmentation methods are highly sensitive to lack homogeneity in objects owing noise intensity inconsistencies. Under such conditions, most approaches exhibit poor quality performance. This paper proposes agent-based model approach for homogenization images reduce presence noisy pixels undesirable artifacts. In our approach, pixel represents agent, set rules evaluates states neighboring agents modify values iteratively until different from assume homogeneous grayscale levels. The proposed method has been used combination with Otsu’s evaluate its performance segmentation. was evaluated types considering their homogeneity. Experimental results indicated that produces better-segmented terms robustness.