Adaptive Threshold Edge Detection Algorithm Based on Neutrosophic Set
To enhance the speed,accuracy,and noise resistance of edge detection,an adaptive threshold edge detection algorithm based on the Neutrosophic Set(NS)is proposed.This algorithm employs a side-window filtering approach to replace traditional filtering algorithms for noise reduction.The NS acquisition algorithm is improved by dividing the image into three subsets:True(T),False(F),and Indeterminate(I),thereby reducing processing time.An adaptive threshold extraction algorithm is introduced to shorten the threshold extraction process.Finally,the segmentation information is fused to obtain the edge features.Experimental results demonstrate that this algorithm outperforms the newly studied Neutrosophic Set and Maximum Norm Entropy(NMNE)edge detection algorithm when dealing with various types of noise.It significantly improves detection speed while ensuring accuracy.
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