计算机工程与科学2013，Vol.35Issue(2)：154-158,5.DOI:10.3969/j.issn.1007-130X.2013.02.027
一种结合多特征的SVM图像分割方法
An SVM image segmentation method using multi-features
摘要
Abstract
Therefore, after analyzing the importance of frequency domain phase information and tex-tural information in characterizing image features, a novel SVM image segmentation method is proposed using phase consistency and textural features. The new method combines phase consistency statistic characteristics, textural features and gray-level characteristics into a training eigenvector and segments image with SVM classification technique. Compared with the traditional method, the statistical eigenvectors extracted by the new method can reflect details of the edges of image and textural information effectively. The experimental results show that the new method is more effective than the traditional method for SVM image segmentation, especially in the situation where there is low edge contrast and rich textural information in the image's target area.关键词
图像分割/相位一致/纹理特征/支持向量机Key words
image segmentation/phase consistency/textural features/SVM分类
信息技术与安全科学引用本文复制引用
邓晓飞,徐蔚鸿..一种结合多特征的SVM图像分割方法[J].计算机工程与科学,2013,35(2):154-158,5.基金项目
国家教育部重点科研基金资助项目(208098) （208098）
湖南省教育厅重点科研基金资助项目(07A056) （07A056）
