苏州科技学院学报（自然科学版）2016，Vol.33Issue(2)：45-50,6.
基于改进水平集方法的腐蚀材料图像特征提取
Feature extraction from corrosion material images via improved level set method
摘要
Abstract
Level set has been widely applied to image segmentation because of its good stability and topological independence. For the rust spot features of material corrosion ,we adopted the level set method without initializing and introduced the Log operator and the Dog operator to the boundary tracking function to strengthen the edge detection extreme value point with the feature detection method of different-scale spacial theory. Based on all this,we extracted the corrosion rust spots of the material images. Through theoretical analysis and simulation ex-periments,the results show that the unimproved method is prone to excessive segmentation in the feature extrac-tion of corrosion rust spots when iterations are too low ,while the improved method is more stable and takes better extraction effect. In addition,the improved method has sped up by 22.9% when the segmentation effects are the same.关键词
水平集/腐蚀锈点/图像分割/特征提取Key words
level set/corrosion rust spot/image segmentation/feature extraction分类
信息技术与安全科学引用本文复制引用
彭丽丽,吴萍萍..基于改进水平集方法的腐蚀材料图像特征提取[J].苏州科技学院学报（自然科学版）,2016,33(2):45-50,6.基金项目
原国防科工委基金资助项目 （）
