Notice of RetractionResearch on fitness function for surface defect feature selection of steel plate

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.

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As variety of surface defect types of steel plates, it is very impendent to find a feature set from original feature set extracted from surface defects, which can express essence characters of defects more effectively and improve defect recognition rate. To settle the problem, genetic algorithm especially fitness function was researched here for the application to defect feature selection on the basis of fully research of theory of information entropy, and average net classification information was used as a fitness function of genetic algorithm to make up for the shortage of using mutual information entropy as fitness function of genetic algorithm. Experiments showed that using optimized feature by genetic algorithm to classify surface defects of steel plates, a higher accurate recognition rate can be achieved.