关键词: 图像分割, 非下采样轮廓变换, 灰度共生矩阵, 特征提取, 特征融合

Abstract: Feature extraction is a key problem for the mass CT image segmentation, a novel features extraction algorithm of CT image is proposed based on Non-Subsampled Contourlet Transform（NSCT） and Gray Level Co-occurrence Matrix（GLCM） in this paper. Firstly, CT image is multi-scale, multi direction decomposed by the NSCT, and the co-occurrence features of sub-images are extracted by GLCM, and then the redundant features are eliminated by the principal component analysis and feature vectors are composed, finally CT image is segmented by the support vector machine based on multi-feature vector space. The experimental results show that the proposed algorithm can extract features of CT image, and has improved the segmentation accuracy of CT images, can provide assisted information for the doctor diagnosis.

Key words: image segmentation, non-subsampled contourlet transform, gray level co-occurrence matrix, feature extracted, features fusion