Title
Automatic band selection for wavelet reconstruction in the application of defect detection
Abstract
In this paper, we present a multiresolution approach for the inspection of local defects embedded in homogeneously textured surfaces. It is based on an efficient image restoration scheme using the wavelet transforms. By properly selecting the smooth subimage or the combination of detail subimages at different resolution levels for image reconstruction, the global repetitive texture pattern can be effectively removed and only local anomalies are preserved in the restored image. A wavelet band selection procedure is developed to automatically determine the best reconstruction parameters based on the energy distribution of wavelet coefficients. Experimental results show that the decomposed subimages and the number of resolution levels determined by the automatic band selection scheme are similar to the manual selection results, and the defects in a variety of real textures including machined surfaces, natural wood, sandpaper and textile fabrics are well detected.
Year
DOI
Venue
2003
10.1016/S0262-8856(03)00003-9
Image and Vision Computing
Keywords
Field
DocType
Surface inspection,Defect detection,Textured image,Wavelet transform,Band selection
Iterative reconstruction,Computer vision,Band selection,Pattern recognition,Wavelet reconstruction,Artificial intelligence,Image restoration,Mathematics,Sandpaper,Energy distribution,Wavelet,Wavelet transform
Journal
Volume
Issue
ISSN
21
5
0262-8856
Citations 
PageRank 
References 
15
0.85
18
Authors
2
Name
Order
Citations
PageRank
Du-Ming Tsai197068.17
Cheng-Huei Chiang2413.00