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2D Iteratively Reweighted Least Squares Lattice Algorithm and Its Application to Defect Detection in Textured Images
Ruen MEYLAN Cenker ODEN Ayn ERTUZUN Aytul ERÇL
Publication
IEICE TRANSACTIONS on Fundamentals of Electronics, Communications and Computer Sciences
Vol.E89A
No.5
pp.14841494 Publication Date: 2006/05/01
Online ISSN: 17451337
Print ISSN: 09168508
Type of Manuscript: PAPER Category: Image Keyword: robust least squares lattice algorithm , 2D lattice filters , texture analysis , defect detection ,
Full Text: PDF(1.2MB) >>Buy this Article
Summary:
In this paper, a 2D iteratively reweighted least squares lattice algorithm, which is robust to the outliers, is introduced and is applied to defect detection problem in textured images. First, the philosophy of using different optimization functions that results in weighted least squares solution in the theory of 1D robust regression is extended to 2D. Then a new algorithm is derived which combines 2D robust regression concepts with the 2D recursive least squares lattice algorithm. With this approach, whatever the probability distribution of the prediction error may be, small weights are assigned to the outliers so that the least squares algorithm will be less sensitive to the outliers. Implementation of the proposed iteratively reweighted least squares lattice algorithm to the problem of defect detection in textured images is then considered. The performance evaluation, in terms of defect detection rate, demonstrates the importance of the proposed algorithm in reducing the effect of the outliers that generally correspond to false alarms in classification of textures as defective or nondefective.

