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- W2353846027 abstract "Considering the fact that the fact that the feature of image for burden surface temperature profile in BF can not be accurately extracted,a kind of maximum fuzzy-entropy image segmentation method based on the multi-source information fusion and the immune genetic algorithm for burden surface infrared image was proposed.Firstly,according to the expert experience and the multi-source detected information of the BF,the image of burden surface was divided into two sub-images,named as high or low temperature sub-image.Then the two sub-images were segmented respectively by using the maximum fuzzy-entropy and the immune genetic algorithm.Finally,the two segmented sub-images were fused into one image.The results show that since both the multi-source information and the temperature feature of the image are thoroughly taken into account,this method makes full use of the advantages of maximum fuzzy-entropy with the high precision and less influence from the target size,and by adopting the immune algorithm,it also improves the convergence speed of genetic algorithm for searching optimal segmentation threshold.The method is effective and accurate to obtain its temperature feature and more timely to discover its abnormal conditions.It is proved to be a better method to meet the demands of the industrial application." @default.
- W2353846027 created "2016-06-24" @default.
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- W2353846027 date "2011-01-01" @default.
- W2353846027 modified "2023-09-23" @default.
- W2353846027 title "Segmentation method for burden surface infrared image in BF based on multi-source information fusion" @default.
- W2353846027 hasPublicationYear "2011" @default.
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