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Notice of Retraction
After careful and considered review of the content of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE's Publication Principles.
We hereby retract the content of this paper. Reasonable effort should be made to remove all past references to this paper.
The presenting author of this paper has the option to appeal this decision by contacting TPII@ieee.org.
A new method to objectively evaluate seam pucker is brought out in this paper. Firstly, AATCC 88B seam pucker standard pictures are taken by digital camera. After wavelet transform of images, the six parameters that are standard deviation of horizontal, vertical and diagonal detail coefficients on 5th dimension, horizontal detail coefficients and histogram and image entropy are extracted, on 4th are extracted. Then, objective evaluation model of seam pucker based on probabilistic neural network is constructed and its prediction accuracy is more than 90% by test. This prediction model can be used to evaluate seam pucker grades of unknown samples, so that to overcome ambiguity and uncertainty of subjective evaluation.