光照鲁棒的模糊C均值聚类显微图像分割

J4 ›› 2014, Vol. 36 ›› Issue (09): 1750-1753.

光照鲁棒的模糊C均值聚类显微图像分割

魏伟一，蔺想红，高志玲，杨小东

(西北师范大学计算机科学与工程学院，甘肃兰州 730070)

收稿日期:2013-04-08 修回日期:2013-06-08 出版日期:2014-09-25 发布日期:2014-09-25
基金资助:
国家自然科学基金资助项目（61165002）；西北师范大学青年教师科研提升计划资助项目（NWNULKQN1124）

Fuzzy C-means clustering based microscopic
image segmentation with illumination robustness

WEI Weiyi，LIN Xianghong，GAO Zhiling，YANG Xiaodong

(College of Computer Science & Engineering,Northwest Normal University,Lanzhou 730070,China)

Received:2013-04-08 Revised:2013-06-08 Online:2014-09-25 Published:2014-09-25

摘要/Abstract

摘要：

传统的模糊C均值FCM聚类图像分割算法在显微图像分割中由于没有考虑光照不均匀的影响而降低了分割的效果，为此，提出了一种光照鲁棒的FCM显微图像分割算法。该算法用正交基函数的线性组合模拟不均匀光照，并引入到FCM算法的目标函数中，进行图像的模糊分割。算法不仅降低了非均匀光照对分割效果的影响，还可以同步估计不均匀光照场。实验结果表明，该方法非常有效。

关键词: 图像分割, FCM, 非均匀光照, 显微图像

Abstract:

It influences the microscopic image segmentation results that traditional fuzzy Cmeans (FCM) ignores the spatial intensity variations caused by uneven illumination, so a novel FCM based microscopic image segmentation algorithm with illumination robustness is proposed, which models the uneven illumination as a linear combination of a set of orthogonal basis functions. Meanwhile, the energy function in FCM is modified by means of the proposed model to support image fuzzy segmentation. The algorithm can alleviate the impact of uneven illumination on segmentation effect and estimate the uneven illumination fields simultaneously. The experimental results show that the algorithm is high efficient.

Key words: image segmentation;FCM;uneven illumination;microscopic image

魏伟一，蔺想红，高志玲，杨小东. 光照鲁棒的模糊C均值聚类显微图像分割[J]. J4, 2014, 36(09): 1750-1753.

WEI Weiyi，LIN Xianghong，GAO Zhiling，YANG Xiaodong. Fuzzy C-means clustering based microscopic
image segmentation with illumination robustness [J]. J4, 2014, 36(09): 1750-1753.

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