DEFECT DETECTION METHOD

PROBLEM TO BE SOLVED: To provide a defect detection method for performing detection and classification on injurious defects by using an effective feature quantity with respect to local frequency of a luminance signal and directionality of the spread of a defect. SOLUTION: This defect detection metho...

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Bibliographic Details
Main Authors NAKAMOTO SHIGEMI, KAZAMA AKIRA, MATSUFUJI YASUHIRO
Format Patent
LanguageEnglish
Published 20.05.2004
Edition7
Subjects
AUXILIARY OPERATIONS USED IN CONNECTION WITH METAL-WORKINGWITHOUT ESSENTIALLY REMOVING MATERIAL
CALCULATING
COMPUTING
COUNTING
IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIRCHEMICAL OR PHYSICAL PROPERTIES
MANUFACTURE OF METAL SHEETS, WIRE, RODS, TUBES OR PROFILES,OTHERWISE THAN BY ROLLING
MEASURING
MEASURING ANGLES
MEASURING AREAS
MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
MEASURING LENGTH, THICKNESS OR SIMILAR LINEARDIMENSIONS
MECHANICAL METAL-WORKING WITHOUT ESSENTIALLY REMOVINGMATERIAL
PERFORMING OPERATIONS
PHYSICS
PUNCHING METAL
TESTING
TRANSPORTING
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Summary:PROBLEM TO BE SOLVED: To provide a defect detection method for performing detection and classification on injurious defects by using an effective feature quantity with respect to local frequency of a luminance signal and directionality of the spread of a defect. SOLUTION: This defect detection method for detecting a defect developed on a surface of an industrial product by an optical method is characterized by dissolving an image signal acquired by imaging into multiple resolution components by two-dimensional wavelet transform, previously selecting multiple resolution components corresponding to the characteristics of the defect to restore images by two-dimensional inverse wavelet transform, and selectively extracting images of defective and non-defective elements each having an intrinsic local frequency and an intrinsic shape. Edges of a steel sheet can be detected by binarizing the restored images and extracting linear factors by means of Hough transform. Different combinations of the resolution components and the number of remaining pixels of the binarized images can be used. Further, defects can be classified by applying a maximum likelihood determination method to the number of remaining pixels. COPYRIGHT: (C)2004,JPO
Bibliography:Application Number: JP20020311615