基于支持向量机的图像分割算法设计

Algorithm Design of Image Segmentation Based on SVM(Supported Vector Machine)

信息的来源多种多样,其中图像是比较重要的一种。随着信息中越来越多地出现数字图像,如何对其进行处理成为国际上的研究热点。图像处理过程包含有图像编码、图像增强、图像压缩和图像分割等许多环节。近年来,学者们对图像分割问题给予了极大关注。介绍了支持向量机的概念,将图像分割看做像素分类,将支持向量机用于图像的分割,包括样本的选择、特征的提取,训练支持向量机,最终实现了基于支持向量机的图像分割算法。结果表明,支持向量机能够很好地将图像目标分割出来。

The information sources are various, among these sources, image has become a more important one. Along with the increasingly appearing of digital images in information, how to process them has become an international research focus. The image processing include many steps such as image coding, image enhancing, image compressing, and image segmenting, etc. In recent years, scholars have given a lot of attention to the image segmenting. This paper briefly introduces the concept of SVM, regards the image segmenting as the pixel classifying, applies SVM into the image segmenting, which includes the sample selection and feature extraction, and carries out the training of SVM, and finally realizes the image segmenting based on SVM. The results show that SVM can segment the image target from background very well.