Homoscedasticity for defect detection in homogeneous flat surface products

Homoscedasticity of homogeneous flat surface products is a necessary condition for a high quality product. The quality of homogeneous flat surface products, like paper sheets, steel slabs, textiles, and glasses, plays a crucial role in raising the profile of the manufacturing companies. This paper presents a new approach for defect detection using the Levene's test, which is used for testing the homogeneity of variances of samples drawn from the same population. It is assumed that the variances of samples taken from the same population are equal. Occurrence of defects results in a Levene's test measure that is higher than some critical value indicating that the null hypothesis of equal variances is rejected. Noise immunity of the proposed technique is ensured through pre-filtering the fabric image using the Wiener filter that is an edge preserving filter. The robustness to variations of the sliding window size and the structures of fabric is analyzed. The major advantages of the proposed technique are the low computational complexity and noise immunity while maintaining high accuracy.