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25 April 2008Flaw detection and segmentation in textile inspection
We present a new method to automatically segment local defects in a woven fabric that does not require any additional
defect-free reference for comparison. Firstly, the structural features of the repetition pattern of the minimal weave repeat
are extracted from the Fourier spectrum of the sample under inspection. The corresponding peaks are automatically
identified and removed from the fabric frequency spectrum. Secondly, we define a set of multi-scale oriented bandpass
filters, adapted to the specific structure of the sample, that operate in the Fourier domain. The filter design is the key part
of the method. Using the set of filters, local defects can be extracted. Thirdly, the filtered images obtained at different
scales are inverse Fourier transformed, binarized and merged to obtain an output image where flaws are segmented from
the fabric background. The method can be applied to fabrics of uniform color as well as to fabrics woven with threads of
different colors. It is Euclidean motion invariant and texture adaptive and it is useful for automatic inspection both online
and off-line. The whole process is fully automatic and can be implemented either optical or electronically. A variety
of experimental results are presented and discussed.