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基于组合赋权的图像分割灰色评估模型

Gray Evaluation Model of Image Segmentation Based on Combinational Weighting

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摘要

分割评价是改善算法性能的重要途径。针对当前图像分割评价指标不能很好地反映分割结果的问题, 提出组合赋权的灰色评估模型。首先, 在现有典型评价准则中选取概率边缘指数、全局一致性误差、变换信息量3个准则来评价图像分割质量。其次, 提出结合德尔菲法、强制判定法和熵权法的主客观组合赋权法, 使权重既反映观察者主观偏好, 又突显图像客观差异。最后, 利用所提出的模型对测试图像进行综合评价。实验结果表明, 所提出的评价模型更符合主观评价结果与地面真实结果。将此模型用于比较基于花粉算法、遗传算法、蛙跳算法的最大熵阈值算法所得到的分割图, 与最大熵的排序结果一致, 进一步验证了该模型的有效性。

Abstract

Segmentation evaluation is an important way to improve the performance of algorithms. A gray evaluation model is proposed based on combinational weighting, aiming at the problem that the current index of image segmentation can not reflect the results of segmentation well. Firstly, variation of information, global consistency error, and probabilistic rand index are selected to evaluate the quality of image segmentation. Secondly, a subjective and objective combinational weighting method is proposed which combines Delphi method, forced decision method, and entropy method. The weights not only reflect the subjective preferences of observers, but also highlight the objective differences of images. Finally, the proposed model is used to make a comprehensive evaluation of test images. Experimental results show that the proposed evaluation model is consistent with the subjective evaluation results and the real ground results. Moreover, this model is used to compare the segmentation results of the maximum entropy threshold algorithms based on flower pollination algorithm, genetic algorithm, and shuffled frog leaping algorithm, respectively. The obtained rank is consistent with the result of maximum entropy, which further validates the effectiveness of this model.

Newport宣传-MKS新实验室计划
补充资料

中图分类号:TP391

DOI:10.3788/lop55.061008

所属栏目:图像处理

基金项目:国家自然科学基金青年基金(11501436)、陕西省软科学研究计划(2014KRM2801)、西安市教育科技重大招标项目(2015ZB-ZY04)、陕西省教育厅科研计划项目(16JK1326, 17JK0340)

收稿日期:2017-11-24

修改稿日期:2017-12-22

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薛菁菁:西安工程大学理学院, 陕西 西安 710048
贺兴时:西安工程大学理学院, 陕西 西安 710048
冯颖:西安工程大学理学院, 陕西 西安 710048
贺飞跃:西安工程大学理学院, 陕西 西安 710048

联系人作者:薛菁菁(810337070@qq.com)

备注:薛菁菁(1992-), 女, 硕士研究生, 主要从事智能优化、图像处理方面的研究。 E-mail: 810337070@qq.com

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引用该论文

Xue Jingjing,He Xingshi,Feng Ying,He Feiyue. Gray Evaluation Model of Image Segmentation Based on Combinational Weighting[J]. Laser & Optoelectronics Progress, 2018, 55(6): 061008

薛菁菁,贺兴时,冯颖,贺飞跃. 基于组合赋权的图像分割灰色评估模型[J]. 激光与光电子学进展, 2018, 55(6): 061008

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