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In order to detect the skew value of fabrics online, a weft skew detection algorithm based on machine vision is studied. Firstly, for the sake of the more prominent weft yarn of the texture , an improved notch filter is used to preprocess the fabric image in the frequency domain. Then the autocorrelation image is calculated to initially extract texture primitives. A large Sobel edge detection template is constructed to extract the weft texture with the Blob analysis. With the texture domain transformed into the parameter space, analyzing the parameter space image with Hessina Matrix is beneficial to obtain the threshold of line detection by the mean of threshold approximation. Finally, the transformation is reversed to display all detected weft skew angles. The camera detection hardware system and the software inference were built to carry out the detection on both high density and low density fabrics. The result showed that the mean absolute deviation was less than 0.35°and the average running time was less than 225.5 ms, which could meet the practical work application required of the weft straightener.