Dissimilarity-based algorithms for fabric defects detection.

The paper investigates images of textures with a defect, characterized by a sufficiently prominent structure. A procedure for detecting a defect in a textured image using an intellectual procedure for assessing the similarity of different parts of the tested image scanned with a sliding window is proposed. It is assumed that an area of the image that contains a defect in whole or in part will be the least similar to the other areas considered. To assess the similarity of images in the paper, the previously proposed measures are used, built on the basis of the values of the components and the magnitude of the gradient, considered as a sample from a random variable with the Weibull distribution. The effectiveness of the proposed methods is demonstrated by experimental investigation. [ABSTRACT FROM AUTHOR]