自动化学报Issue(5)：883-891,9.DOI:10.3724/SP.J.1004.2014.00883
基于监督双限制连接Isomap算法的带钢表面缺陷图像分类方法
Strip Surface Defect Image Classification Based on Double-limited and Supervised-connect Isomap Algorithm
摘要
Abstract
A double-limited and supervised-connect Isomap dimensionality reduction and classification method (dls-Isomap) is proposed in this paper to classify more accurately the stripe surface defect images with the typical characteristics of complex texture, much noise, and high-dimension non-linear geometry. Based on the dimensionality reduction technique from Isomap, the connection of neighborhood graph is limited by key parameters K-nearest neighbor (KNN) andε-radius, and inter-class neighborhood points are connected extensionally with the supervision of class labels. According to multi-classes roll-swiss data experiments, all the points can be embedded in lower dimensions with the complete inter-class and intra-class geometric structure, and the“short circuit”in the Isomap can be solved by the dls-Isomap method. In addition, stripe surface defect images data experiments show that the proposed classification method is suitable for the classification of stripe surface defects including more water and oil, with a recognition rate of 78%for cold-roll strip images, and 93%for hot-roll strip images with water, among which the recognition rata of water defects is 97.6%.关键词
Isomap/K领域/ε-半径/监督连接/带钢表面缺陷Key words
Isomap/K-nearest neighbor (KNN)/ε-radius/supervised-connect/stripe surface defect引用本文复制引用
王典洪,甘胜丰,张伟民,雷维新..基于监督双限制连接Isomap算法的带钢表面缺陷图像分类方法[J].自动化学报,2014,(5):883-891,9.基金项目
国家自然科学基金(61271274),湖北省自然科学基金(2012FKB6416)资助 （61271274）
Supported by National Natural Science Foundation of China (61271274) and Natural Science Foundation of Hubei Province (2012FKB6416) （61271274）
