Texture defect detection method based on H-image and Hotteling model T2

In this paper we have proposed a new defect detection algorithm based on local homogeneity and hotteling model to localize defects in various textures images. Firstly, the local homogeneity of each pixel is computed to construct a new homogeneity image denoted as (h-image). Then a wavelet transform, in order to extract features details, is applied. After, these energy are integrated by the hotelling's t-squared statistic and the defect blocks can be determined by the multivariate statistical method. Finally, a simple thresholding method is applied to set a threshold for distinguishing between defective areas and uniform regions. Simulations on different textured images show good promising results. This new automatic defect detection method shows good performance in comparison with other existing algorithms.