Feature Extraction and Classification Examination of Lung Image Based on Pseudo-zernike Invariant Moment

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.