A fuzzy morphological hit-or-miss transform for grey-level images: A new approach

González-Hidalgo, Manuel; Massanet, Sebastià; Mir, Arnau; Ruiz-Aguilera, Daniel

doi:10.1016/j.fss.2015.01.014

Cited by 13 publications

(2 citation statements)

References 42 publications

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“…This paper uses the fuzzy mathematical morphology, which is based on fuzzy conjunctions and fuzzy implication functions. It was introduced in [17], and it was used successfully in many applications (see [14,18]). We recall the definitions of fuzzy logic operators that are used in this framework (see [19][20][21]).…”

Section: Fuzzy Logic and Fuzzy Morphological Operatorsmentioning

confidence: 99%

Impulsive Noise Removal with an Adaptive Weighted Arithmetic Mean Operator for Any Noise Density

et al. 2021

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Many computer vision algorithms which are not robust to noise incorporate a noise removal stage in their workflow to avoid distortions in the final result. In the last decade, many filters for salt-and-pepper noise removal have been proposed. In this paper, a novel filter based on the weighted arithmetic mean aggregation function and the fuzzy mathematical morphology is proposed. The performance of the proposed filter is highly competitive when compared with other state-of-the-art filters regardless of the amount of salt-and-pepper noise present in the image, achieving notable results for any noise density from 5% to 98%. A statistical analysis based on some objective restoration measures supports that this filter surpasses several state-of-the-art filters for most of the noise levels considered in the comparison experiments.

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Section: Fuzzy Logic and Fuzzy Morphological Operatorsmentioning

confidence: 99%

Impulsive Noise Removal with an Adaptive Weighted Arithmetic Mean Operator for Any Noise Density

et al. 2021

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“…Since then, several important classes of fuzzy negations have been proposed with different motivations, as we can see in [22,23,26,28,34,38]. Fuzzy negations have applications in several areas, such as decision making, stock investment, computing with words, mathematical morphology and associative memory, as the presented in [8,10,23,25,40,43].…”

Section: Introductionmentioning

confidence: 99%

Ordinal Sums of Fuzzy Negations: Main Classes and Natural Negations

de Lima,

Bedregal,

Mezzomo

2019

Preprint

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In the context of fuzzy logic, ordinal sums provide a method for constructing new functions from existing functions, which can be triangular norms, triangular conorms, fuzzy negations, copulas, overlaps, uninorms, fuzzy implications, among others. As our main contribution, we establish conditions for the ordinal sum of a family of fuzzy negations to be a fuzzy negation of a specific class, such as strong, strict, continuous, invertible and frontier. Also, we relate the natural negation of the ordinal sum on families of t-norms, t-conorms and fuzzy implications with the ordinal sum of the natural negations of the respective families of t-norms, tconorms and fuzzy implications. This motivated us to introduces a new kind of ordinal sum for families of fuzzy implications.

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