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Ancient Chinese Character Image Retrieval Based on Dual Hesitant Fuzzy Sets
Author(s) -
Songbo Du,
Fang Yang,
Xuedong Tian
Publication year - 2021
Publication title -
scientific programming
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.269
H-Index - 36
eISSN - 1875-919X
pISSN - 1058-9244
DOI - 10.1155/2021/6621037
Subject(s) - dual (grammatical number) , character (mathematics) , pattern recognition (psychology) , artificial intelligence , fuzzy logic , computer science , similarity (geometry) , chinese characters , image (mathematics) , membership function , entropy (arrow of time) , mathematics , fuzzy set , data mining , art , physics , geometry , literature , quantum mechanics
,e complex and changeable structures of ancient Chinese characters result in the decreasing accuracy of their image retrieval. To resolve this problem, a new retrieval method based on dual hesitant fuzzy sets is proposed. Dual hesitation fuzzy sets that can express uncertain information more comprehensively are employed in the feature extraction process of directional line elements. ,emultiattribute evaluation index of adjacent grids for the current grid and its corresponding membership and nonmembership functions are established, and the weight of each attribute is calculated by the dual hesitation fuzzy entropy, such that the proposed features can fully reflect the topological structure of ancient Chinese characters. Using the dual hesitation fuzzy correlation coefficient to measure the similarity between the ancient Chinese character images to be retrieved and the candidate images, the retrieval of ancient Chinese character images is realized. Experiments show that when the t0hreshold value of the correlation coefficient is 0.9, the average retrieval accuracy is 90.4%.

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