3D RECONSTRUCTION MODEL OF METAL FRACTURE SEM IMAGE AND REALIZATION

摘要：

In this paper, a new neural-based reflectance model of the Scanning Electron Microscope (SEM) image is proposed.The idea of this method is to adapt imaging mechanism of real secondary electron SEM.The conventional cost function is modified, which smoothness constraint is replaced by fractal constraint The proposed method overcomes the disadvantage of tradition shape from shading algorithm.The detail features of metal fracture surface are reconstructed better.The contrastive experiments are performed by the conventional SFS model and our new model.The maximum brightness error of SEM image is decreased from 23.84％ to 6.28％ and the average brightness error is decreased from 4.46％ to 1.07％.The experimental results show that the algorithm is very efficiency and accuracy for single metal fracture SEM image of the unknown light source direction.

关键词： Metal fracture SEM Neural network 3D reconstruction Fractal

作者: GE-WEN KANG WEN-WEI REN HENG-LI CHEN

作者单位: School of Automation Engineering, University of Electronic Science and Technology of China, Chengdu, 610054

会议类型: 国际会议

会议名称: 2007 International Conference on Machine Learning and Cybernetics(IEEE第六届机器学习与控制论国际会议)

会议地点: 香港

会议语种:英文

页码: 1753-1758

在线出版日期: 2007-08-19（万方平台首次上网日期，不代表论文的发表时间）