Automated Inspection of Steel Structures

In this paper, the problem of automatic classification of rus t grades on steel surfaces is considered. Three texture analysis metho ds are studied to form features from steel surfaces. Nearest Neighbor cla ssifier is used for classification of steel surface types. The results indicat e that automation of the inspection and classification process is feasible.

[1]  C. Ünsalan.  CLASSIFICATION OF RUST GRADES ON STEEL SURFACES PART 2 , 1997 .

[2]  Wei-Chung Lin,et al.  Metal surface inspection using image processing techniques , 1984, IEEE Transactions on Systems, Man, and Cybernetics.

[3]  Rama Chellappa,et al.  Multiresolution Gauss-Markov random field models for texture segmentation , 1997, IEEE Trans. Image Process..

[4]  Milan Sonka,et al.  Image Processing, Analysis and Machine Vision , 1993, Springer US.

[5]  R. Haralick,et al.  Computer Classification of Reservoir Sandstones , 1973 .

[6]  Robert M. Haralick,et al.  Textural Features for Image Classification , 1973, IEEE Trans. Syst. Man Cybern..

[7]  Anil K. Jain,et al.  Markov Random Field Texture Models , 1983, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[8]  Luc Van Gool,et al.  Texture analysis Anno 1983 , 1985, Comput. Vis. Graph. Image Process..

[9]  Richard W. Conners,et al.  Identifying and Locating Surface Defects in Wood: Part of an Automated Lumber Processing System , 1983, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[10]  Zhigang Fan,et al.  Automated Inspection of Textile Fabrics Using Textural Models , 1991, IEEE Trans. Pattern Anal. Mach. Intell..