文献类型：期刊文献

英文题名：Segmentation by local binary fitting active contour model for activated carbon fibers material microscopic images

作者：Zhao, Jiang Kun[1]; Zhu, Yu[1]; Yu, Jian Feng[1]

机构：[1] School of Information Science and Engineering, East China University of Science and Technology, Shanghai, China

年份：2013

卷号：811

起止页码：370

外文期刊名：Advanced Materials Research

收录：EI(收录号：20134516945603)

语种：英文

外文关键词：Numerical methods - Carbon fibers - Activated carbon

摘要：Many bubbles and pores are appeared on Activated Carbon Fibers (ACFs) material microscopic images. The morphology of ACFs surface image is complicated. Some widely used traditional methods are difficult to segment the object correctly. In this paper, an implicit active contour driven by local binary fitting energy is used to segment the objects for ACFs micro-images. This method is based on local image edge information to obtain optimal level set active contour model. Experimental results show that this active contour model is flexible for analyzing images with complex porous structure. ? (2013) Trans Tech Publications, Switzerland.