Texture inspection with self-adaptive convolution filters

A resolution-independent method for detection of imperfections in quasi-periodic textures is described. After image standardization, the period is estimated in the horizontal and vertical directions. This determines the size of a sparse convolution mask. Mask coefficients are determined by the well-known technique of eigenfilter extraction. The method thus offers a completely automated generation of a bank of suitable filters, the form and the coefficients of which are made dependent on the texture type to be inspected. After feature extraction in the filtered images, a Mahalanobis classifier is applied.<
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