Metal Surface Inspection Using Image Processing Techniques

Hon Son Don, King Sun Fu, Wei Chung Lin

Research output: Contribution to journalArticlepeer-review

36 Scopus citations


The feasibility of applying image processing techniques to metal surface inspection is demonstrated. Two methods for metal surface inspection are described. In the first method, the metal surface reflective power and the metal surface normal are related by a random surface scattering model. The metal surface profile can then be computed from metal surface normal. The second method applies pattern recognition techniques to classify metal surfaces into classes of different roughness. Methods of feature extraction and classification have been tested experimentally and the performances of different types of classifier have been compared. A two-level tree classifier using nonparametric linear classifiers at each node gives better than 90 percent correct classification on our testing set.

Original languageEnglish (US)
Pages (from-to)139-146
Number of pages8
JournalIEEE Transactions on Systems, Man and Cybernetics
Issue number1
StatePublished - Jan 1 1984

ASJC Scopus subject areas

  • Engineering(all)

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