FLAW TYPE CLASSIFICATION BOUNDARY SETTING METHOD IN SURFACE DEFECT DETECTION, AND DEFECT DETECTION METHOD

摘要

PROBLEM TO BE SOLVED: To provide a flaw type classification boundary setting method in surface defect detection allowing even an operator without having a special technique to simply realize complicated defect classification, and enabling evaluation capable of remarkably reducing work and of rapidly responding to change of an operation state.

SOLUTION: Feature data are inputted for every flaw type (steps S11-S14); parameters (the average vector, a covariance matrix and a coupling coefficient) of a mixture density distribution for every flaw type are found (step S15); an identification boundary for every flaw is determined by using Bayes' theorem based on the found mixture density distribution for every flaw type (step S16); and the likelihood of the determination is calculated (step S17).

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