Title :
Texture defect detection method based on H-image and Hotteling model T2
Author :
Rebhi, Ali ; Abid, Sabeur ; Fnaiech, Farhat
Author_Institution :
Sci. Res. Lab. in Signal, Image Process. & Energy Control, SIME Univ. of Tunis, Tunis, Tunisia
Abstract :
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.
Keywords :
feature extraction; image segmentation; image texture; manufacturing processes; object detection; production engineering computing; quality control; statistical analysis; wavelet transforms; H-image; Hotelling t-squared statistic; Hotteling model T2; defect block determination; defect localization; feature extraction; local homogeneity; manufacturing processes; multivariate statistical method; quality control; texture defect detection method; texture image; thresholding method; wavelet transform; Feature extraction; Gabor filters; Image segmentation; Inspection; Vectors; Wavelet transforms; Defect detection; Hotteling model T2; local homogeneity (H-image); texture image;
Conference_Titel :
Advanced Technologies for Signal and Image Processing (ATSIP), 2014 1st International Conference on
Conference_Location :
Sousse
DOI :
10.1109/ATSIP.2014.6834589