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Details of the recordtitle  2D iteratively reweighted least squares lattice algorithm and its application to defect detection in textured images  authors  Meylani, Ruşen and Öden, Cenker and Ertüzün, Ayşin and Erçil, Aytül  keywords   abstract  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.  type  Journal Paper  journal  IEICE transactions on fundamentals of electronics, communications and computer sciences , E89A (5). pp. 14841494  published year  2006  serial  1777  is_viewable  yes 

