摘要
基于模板匹配的图像分割算法在显微细胞图像分割中具有很好的通用性。针对传统模板匹配显微细胞图像分割算法在创建模板集时会产生较多冗余模板,造成图像分割时间过长的问题,提出一种改进的模板匹配显微细胞图像分割算法。本算法在传统模板匹配算法的基础上,提取模板集的形状特征,并计算其相似度;然后在不影响图像分割准确率的情况下,剔除模板集中相似度过高的模板来精简模板集;最后利用精简模板集分割测试图像。通过对U2OS图像集和NIH3T3图像集进行实验,结果表明改进算法在保持准确率与传统算法相当的情况下,具有比传统算法更快的运行速度和更好的性能。
Image segmentation algorithm based on template matching has good generality in the microscopic cell image segmentation. In view of the traditional template matching microscopic cell image segmentation algorithm in producing template set produced more redundant templates, which led to a rather long time of image segmentation, an improved template matching microscopic cell image segmentation algorithm was proposed. This algorithm extracted shape feature and calculated similarity of template set on the basis of the traditional template matching algorithm. Then, this algorithm eliminated the more similar templates to reduce template set in the case of least affecting the accuracy of image segmentation. Finally, the reduced template set was used to complete the segmentation. The experiments on U2OS and NIH3T3 image sets show that the improved algorithm is comparable with traditional algorithm in accuracy, and has faster speed and better performance compared with traditional algorithm in image segmentation.
出处
《计算机与现代化》
2015年第8期1-7,12,共8页
Computer and Modernization
基金
国家自然科学基金资助项目(61073058
61201347)
重庆市科委自然科学基金计划资助项目(cstc2012jj A40011)
关键词
细胞图像分割
模板匹配
精简模板集
形状特征提取
cell image segmentation
template matching
reduced template sets
shape feature extraction
作者简介
葛亮（1980-），男，重庆人，重庆大学计算机学院副教授，硕士生导师，博士，研究方向：计算机视觉，数据挖掘，Web应用技术；
于卡（1989-），女，河南新乡人，硕士研究生，研究方向：数字图像处理。
