【摘要】 以形态学分析和支持向量机为基础,构建了一套血细胞核显微图像自动分析与识别系统。在细胞核分割阶段,提出基于支持向量机的血液细胞核彩色图像分割算法。在特征提取环节中,除使用常规形态特征外,提出了一种新的能有效反映核分叶数差异的形态特征——腐蚀退化因子。采用"one-against-one"策略的多分类SVM方法对血细胞进行分类识别。实验测试表明,该系统具有较高的识别精度,平均识别率达94.13%。更多还原

【Abstract】 Based on morphological analysis and Support Vector Machines (SVM),a robust automatic analysis system of blood cell nuclei is developed. A novel algorithm for color image segmentation of blood cell nuclei based on the SVM is proposed. A new morphological feature named erosion degenerate factor is used to indicate the lobulated state of cell and achieves feature extraction by combining with traditional characteristics. One-against-one multi-class SVM is applied to classify the blood cell. Experimental results show that the proposed system yields better performance with the average recognition rate of 94.13%.更多还原