摘要
提出了应用图像关联度的图像模糊分类新方法。该方法在求得每幅图像相对各个类别的关联度的基础上,求得每个类别图像关联度的均值和标准差σ;然后计算每幅图像的关联度与所在类别关联度均值之差Δi,差值Δi≤2σ,该图像应"留"在该类中;否则,该图像应归入与另两个类别的关联度较大的类别。每幅图像都经过这样的检验,实现图像的再划分,直到这一过程稳定为止。实验结果表明,该方法的图像分类质量有一定优势。
We propose a new image fuzzy classification method which based on the image relational de- gree. The correlation degree basis points are obtained in each category , and the mean and standard deviation a of relational degree are calculated for each category. Then the correlation degree for each image and the mean difference of correlation degree for each category &i are calculated. If △i≤2a, the image should "stay" in the class, otherwise, the image should be associated with a greater correlation degree of the other two categories. Each image should have such inspection to achieve image re-divi- sion until the process is stable. Comparison results show that the quality of the quality of the image classification method has certain advantages.
出处
《武汉大学学报(信息科学版)》
EI
CSCD
北大核心
2015年第5期574-577,共4页
Geomatics and Information Science of Wuhan University
基金
国家973计划资助项目(2012CB719905)~~
关键词
图像关联度
图像模糊分类
图像分类
image correlation degree
image fuzzy classification
image classification