Method and apparatus for analyzing an image to detect and identify defects

A method for detecting and identifying defects in an object comprising the steps of:

• storing the digital representation of the image in memory;
• transforming the digital representation by performing a transformation process which extracts certain defect feature sets contained in the image of the object;
• the transforming step including convolving the digital representation with a series of wavelets;
• wherein the resulting wavelet coefficients comprise the defect features;
• creating fuzzy sets by calculating the degree of membership of the extracted features with stored feature templates according to a similarity function;
• and
• using the fuzzy sets in a fuzzy inferencing scheme to infer and classify whether a defect has been detected and, if so, the type of defect that has occurred;
• wherein the fuzzy wavelet coefficients are compared with fuzzy sets stored as representative features in a knowledge base for different wavelet scales and for a plurality of anticipated defects and wherein the wavelet scales are selected to maximize detectability and identifiability measures.

An apparatus for analyzing an image of a fabric to detect and identify defects in the fabric, said apparatus comprising:

• at least one image sensor disposed to capture the image of at least part of the fabric;
• a light source for projecting light through the fabric;
• means for converting the captured image into a 2D digital representation;
• a storage device for receiving said 2D digital representation of the image from said converting means and for storing said digital representation;
• and
• processing means for processing said 2D digital representation of the captured image, said processing means including means for converting said 2D digital representation into at least one ID scan of the image which is particularly adapted to detect an expected defect type, means for convolving said at least one 1D scan of said image with at least one predetermined wavelet from a firmly of wavelets to extract certain defect features in the form of wavelet coefficients from said at east one 1D digital representation means for concerting said wavelet coefficients into fuzzy sets via a similarity transformation, and means for declaring and classifying defects based upon said defect features.