Genetic Parameter Tuning for Reliable Segmentation of Colored Visual Tags

This paper reports on a case study on segmentation of colored visual tags for object identification. Lighting variations result in uncertainty in color thresholds leading to unreliable overall system behavior. We describe an experiment with a genetic algorithm (GA) approach for generating reliable thresholds for color identification. We compare it with a maximum distance (MD) approach, and demonstrate that the genetic approach is far more accurate and reliable