摘要
提出一种基于Krawtchouk矩和支持向量机的图像纹理分割方法.对图像的每个像素,选择一个窗口,计算该窗口内的Krawtchouk矩,然后通过非线性变换将得到的矩值转换成纹理特征,对特征空间进行优化后,使用支持向量机进行纹理分割.和基于Zernike矩的纹理分割结果相比,本文的方法能得到更好的纹理分割结果.
A new image texture segmentation method is presented based on the Krawtchouk moments and support vector machine （SVM）. The Krawtchouk moments in small local windows of each pixel in the image are computed and a nonlinear transducer is used to map the moments to texture features. The feature vector is then input to SVM for classification. Compared with the segmentation results based on the Zernike moment, the proposed method can produce better results.
出处
《应用科学学报》
CAS
CSCD
北大核心
2008年第5期521-525,共5页
Journal of Applied Sciences
