一种自适应小目标图像分割方法

An Adaptive Approach to Small Object Segmentation

  • 摘要: 将遗传算法用于小目标图像分割,提出了目标在图像中所占比例的可能范围参数,并结合P-tile法和直方图熵法得到一种新的适应目标分割方法,该方法克服了传统P-tile法要求己知目标所占确切比例的缺陷,并利用遗传算法能自动在搜索空间内快速寻优的特点,可以推广到包含任意大小目标的图像分割问题上,用户可选择目标占整个图像面积的不同的“最小百分比”和“最大百分比”参数进行反复操作,得到多个不同结果,然后对这些结果做后续分析(如数据融合分析),从而得到更加准确的判断,试验结果表明,该方法具有良好的分割质量,运算速度提高21.5%。

     

    Abstract: 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.

     

/

返回文章
返回
Baidu
map