Defect detection in fabrics with a joint transform correlation technique: Theoretical basis and simulation

The theoretical basis of a technique for real time defect detection in fabr ics is presented using a joint transform correlator. This correlation techn ique is an extension of Fourier transform analysis and is extremely useful for real time pattern recognition. The regular periodic nature of a woven f abric makes it possible to use the Fourier transform technique to detect de fects. However, classifying various defect types is difficult from the Four ier analytical and experimental results. A solution to this problem is to u se a joint Fourier transform of a reference pattern and the test pattern, a nd the joint power spectrum is further processed. Cross- and auto-correlati on peaks, generated after the execution of the second Fourier transform on the filtered joint power spectrum, indicate the existence of a particular d efect type. Because of the parallel processing ability of the optical syste m, implementing the joint transform correlation technique in an optical dom ain is advantageous. A fractional power fringe adjusted filter is used for efficient detection of defects. The mathematical formulation of the techniq ue is supported by the simulated results for identifying some defects such as the existence of thick yarns, knots, and missing yarns.