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- W4288042013 abstract "Abstract In image processing, edge detection is extremely important especially in feature detection. An edge detection algorithm for neutrosophic set based on adaptive threshold is proposed to effectively filter out the large amount of noise in the image and improve the detection speed and accuracy. The algorithm uses side window filtering algorithm to filter out noise based on neutrosophic set; Furthermore, it modifies the subset segmentation algorithm to split the image into three subsets of T, F, I; Then, an adaptive threshold extraction algorithm is proposed to segment the subset information; Finally, the segmentation information is merged to obtain edge features. In order to verify the effectiveness of the algorithm, an experiment is compared with the neutrosophic set edge detection algorithm based on maximum entropy (NMNE) under different noise conditions. An experimental comparison between Canny and Sober is also carried out additionally. Experimental results show that the algorithm has good anti-noise performance and improves the detection speed and accuracy of the neutrosophic set edge detection algorithm based on maximum entropy (NMNE). The algorithm proposed in this paper can provide an effective reference for mid- and high-level vision tasks." @default.
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- W4288042013 date "2022-07-26" @default.
- W4288042013 modified "2023-10-17" @default.
- W4288042013 title "An edge detection algorithm for neutrosophic set based on adaptive threshold" @default.
- W4288042013 doi "https://doi.org/10.21203/rs.3.rs-1860703/v1" @default.
- W4288042013 hasPublicationYear "2022" @default.
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