西安科技大学学报2017，Vol.37Issue(5)：731-735,5.DOI:10.13800/j.cnki.xakjdxxb.2017.0520
基于超像素特征表示的图像前景背景分割算法
Foreground and background segmentation based on superpiexel-level feature representation
薛萍1
作者信息
- 1. 西安科技大学计算机科学与技术学院,陕西西安710054
- 折叠
摘要
Abstract
The foreground and background segmentation is an important technique in image processing.In this paper,a binary segmentation method is proposed based on the classification of superpixel.The input image is firstly divided into several superpixel to protect the edge of objects.For each superpixel,the color and texture are considered to extract the feature with robust for illumination and color,which can eliminate the influence of light and color.The feature vectors are further used to train a classification to classify the superpixel into foreground or background.Finally,the graph cut method is used to modify the class label of each pixel with the initialization of superpixel.The experiment result shows that the method can successfully extract the objects from the background.Moreover,this method is easy to be implemented since it can be combined with the classification technique directly.关键词
图像分割算法/超像素提取/线性分类器/特征表示Key words
image segmentation/superpixel extraction/linear classifier/feature representation分类
信息技术与安全科学引用本文复制引用
薛萍..基于超像素特征表示的图像前景背景分割算法[J].西安科技大学学报,2017,37(5):731-735,5.
