基于Pseudo-zernike不变矩的肺部图像特征提取及分类研究

摘要

In order to analyse the feature of the lung image accurately and effectively, this paper presents a feature analysis approach of the lung image based on Pseudo-zernike invariant moment. Through the pre-processing and feature extraction of the lung image based on Pseudo-zernike moment invariant, the extraction eigenvalue of the lung image is classified and reaserched using SVM classifier, which has good recognition performance . The experimental results show that this method can characterize the teature of the lung image,and possess good classification accuracy.%为准确、快速地分析肺部图像的特征,提出了一种基于Pseudo-zernike不变矩的肺部特征分析方法.通过对肺部图像进行预处理和基于Pseudo-zernike不变矩的特征提取,利用具有良好识别性能的SVM分类器对提取的肺部图像特征值做分类研究.实验结果表明,该方法能够很好地表征肺部图像的特征,具有良好的分类准确率.