Closed-loop adaptive image segmentation
نویسندگان
چکیده
One of the fundamental weaknesses of current computer vision systems used in outdoor applications is their inability to adapt the segmentation process as real-world changes occur in the image. We present a closed loop image segmentation system that incorporates a genetic algorithm to adapt the segmentation process to changes in image characteristics caused by variable environmental conditions. The genetic algorithm efficiently searches the hyperspace of segmentation parameter combinations to determine the parameter set which maximizes the segmentation quality criteria. We present a summary of the experimental results that demonstrates the ability to perform adaptive image segmentation and to learn from experience using a collection of outdoor color imagery.
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