Image Segmentation Based on Pixel Feature Manifold

摘要：

Image segmentation is an important problem in pattern recognition, computer vision and other related area, which is still a research focus. In this paper, we consider the segmentation as pixel classification scheme and introduce a manifold way to address this problem. Some local features, such as Haar, LBP and SIFT, are used to represent each pixel in the image together with the basic property of the pixel. We put these pixel features on a manifold called pixel feature manifold (PFM) obtained via manifold learning methods and classify pixels with k-NN classifier in the pixel embedding space. Experimental results on MSRC image dataset show that our PFM method can effectively segment images.

关键词： image segmentation image feature Laplacian embedding

作者: Haopeng Zhang Zhiguo Jiang Wei Zhang Danpei Zhao

作者单位: Image Processing Center, School of Astronautics, Beihang University, 37 Xueyuan Road, HaidianDistric Image Processing Center, School of Astronautics, Beihang University, 37 Xueyuan Road, Haidian Distri

会议类型: 国际会议

会议名称: 第七届多光谱图象处理与模式识别国际学术会议

会议地点: 桂林

会议语种:英文

页码: 1-6

在线出版日期: 2011-11-01（万方平台首次上网日期，不代表论文的发表时间）