An Adaptive Approach to Small Object Segmentation

An adaptive approach to small object segmentation based on genetic algorithms is proposed. A new parameter "scale of the object area's percentage" is introduced in this method, which can overcome the P tile method's defect of requiring the exact percentage of an object area, and makes effective use of the small object's character. Genetic algorithm forms the skeleton of the new approach, which can dynamically locate the optical threshold in the search space. The proposed algorithm can be extended to segment those images with object of arbitrary size by simply changing the set of the new parameter. Experiment results indicate that the proposed algorithm has better segmentation quality and improves the computational efficiency by 21 5% compared with the conventional Otsu method.