论文信息 - A New Class of Similarity Measures for Fuzzy Sets

A New Class of Similarity Measures for Fuzzy Sets

Fuzzy techniques can be applied in many domains of computer vision community. The definition of an adequate similarity measure for measuring the similarity between fuzzy sets is of great importance in the field of image processing, image retrieval and pattern recognition. This paper proposes a new class of the similarity measures. The properties, sensitivity and effectiveness of the proposed measures are investigated and tested on real data. Experimental results show that these similarity measures can provide a useful way for measuring the similarity between fuzzy sets.

Saleh Omran | Mahmoud Hassaballah

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