DocumentCode
553940
Title
Notice of Retraction
Study on objective evaluation of seam pucker based on wavelet probabilistic neural network
Author
Li Yanmei ; Qiu Xiaokun ; Jiang Zhenzhen
Author_Institution
Fashion Coll., Shanghai Univ. of Eng. Sci., Shanghai, China
Volume
1
fYear
2011
fDate
26-28 July 2011
Firstpage
259
Lastpage
262
Abstract
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.
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.
Keywords
clothing industry; entropy; image processing; neural nets; probability; production engineering computing; wavelet transforms; digital camera; image entropy; seam pucker; standard deviation; wavelet probabilistic neural network; wavelet transform; Accuracy; Correlation; Predictive models; Probabilistic logic; Wavelet analysis; Wavelet transforms; objective evaluation; probabilistic neural network; seam pucker; wavelet transform;
fLanguage
English
Publisher
ieee
Conference_Titel
Natural Computation (ICNC), 2011 Seventh International Conference on
Conference_Location
Shanghai
ISSN
2157-9555
Print_ISBN
978-1-4244-9950-2
Type
conf
DOI
10.1109/ICNC.2011.6021915
Filename
6021915
Link To Document