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An adaptive approach to small object segmentation

机译:小对象分割的自适应方法

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摘要

An adaptive approach to small object segmentation based on Genetic Algorithms is proposed. A new parameter "scale of the subject 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 meanwhile 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 performs better segmentation quality and takes less computational time than conventional Otsu method.
机译:提出了一种基于遗传算法的小目标自适应分割方法。该方法引入了新的参数“对象区域百分比的比例”,可以克服P-tile方法需要精确的对象区域百分比的缺点,同时可以有效利用小对象的特征。遗传算法构成了新方法的框架,该方法可以在搜索空间中动态定位光学阈值。通过简单地改变新参数的设置,所提出的算法可以扩展为用任意大小的对象分割那些图像。实验结果表明,与传统的Otsu方法相比,该算法具有更好的分割质量和更少的计算时间。

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