Segmentation algorithm for adherent cell images based on edge chain-code information

被引：0

作者：

Zhang, Rui-Hua ^{[1
,2
]}

Wu, Jin ^{[1
]}

机构：

[1] College of Information Science and Engineering, Wuhan University of Science and Technology, Wuhan, Hubei 430081, China

[2] Experiment Center, Air Force Radar Academy, Wuhan, Hubei 430019, China

来源：

Beijing Ligong Daxue Xuebao/Transaction of Beijing Institute of Technology | 2013年 / 33卷 / 07期

关键词：

Adherent cells - Chain codes - Curvature radii - Linear Interpolation - Segmentation algorithms - Segmentation results - Sequence images - Threshold algorithms;

D O I：

暂无

中图分类号：

学科分类号：

摘要：

A segmentation algorithm for adherent cell images based on edge chain-code information is presented in this paper. Firstly, a pre-processing was carried out for the cell image with low contrast ratio. Then edge chain code of cell binary image was used to keep track of their contours and extract their shape features, such as chain code sum, chain code diff, curvature radius and approximate perimeter. Further, the criterion of distinguishing edge inflexion and sleek curve section was provided. In the end, the adherent cell images were separated through linear interpolation between authentic corners. The presented algorithm has been applied to two sequence images with 120 frames. The segmentation results show that proposed algorithm can not only solve the problem of segmentation but also repair cell edge hollow as well as can count the number of cells successfully. Compared with the threshold algorithm and priori model algorithm, this algorithm can improve the success rate by 40%~60%.

引用

页码：747 / 753