摘要
针对尿沉渣图像中的红白细胞,提出了一种基于组合思想的分割方法,即对图像进行三层处理,将各层的分割结果进行融合,从而通过多信息互补的方法得到完整的分割结果。设计了两级集成SVM分类器对红白细胞进行识别。实验证明,提出的整套算法简洁高效,精度高,具有较强的普适性。
A segmentation method based on combination thoughts for the red and white cells in the urine sediment images is proposed, in which images are splitted into three layers, and the segmentation results of each layer are fused to get a com-plete segmentation result through multi-information complementary. Two-level integrated SVM classifier was designed to identify the red and white cells. The experiment results show that the algorithm proposed is not only simple and efficient, but also has high precision and strong universality.
出处
《现代电子技术》
2013年第17期118-121,共4页
Modern Electronics Technique
关键词
尿沉渣
图像分割
多信息互补
SVM
urine sediment
image segmentation
multi-information complementary
SVM
