Fusion Multi-feature Fuzzy Model for Target Recognition and Its Application

In natural recognition scenes, image features are often characterized by complexity, diversity and fuzziness, and lack of consideration of the relationship between features when using multiple features for image recognition, a target recognition fuzzy model integrating multiple image features is pro...

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Bibliographic Details
Published inJi suan ji ke xue Vol. 50; p. 505
Main Authors Ruan, Wang, Hao, Guosheng, Wang, Xia, Hu, Xiaoting, Yang, Zihao
Format Journal Article
LanguageChinese
Published Chongqing Guojia Kexue Jishu Bu 01.01.2023
Subjects
Algorithms
Feature recognition
Fuzzy sets
Particle swarm optimization
Surface defects
Target recognition
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Summary:In natural recognition scenes, image features are often characterized by complexity, diversity and fuzziness, and lack of consideration of the relationship between features when using multiple features for image recognition, a target recognition fuzzy model integrating multiple image features is proposed.Firstly, the image feature is extracted, the value of the feature is taken as the fuzzy set of the model, and the corresponding membership function is given.Secondly, the evaluation index of the model is gi-ven, and the feasibility of the model is demonstrated according to the index.Thirdly, particle swarm optimization algorithm is used to optimize the parameters of membership function of image features.Finally, the target recognition algorithm based on feature fusion fuzzy model is proposed, which is applied to filling-mark recognition and the hot rolled strip surface defect recognition.Experimental results show that the designed model performs well under the evaluation index, and the algorithm significantly
ISSN:1002-137X