Overlap Functions-Based Fuzzy Mathematical Morphological Operators and Their Applications in Image Edge Extraction
As special aggregation functions, overlap functions have been widely used in the soft computing field. In this work, with the aid of overlap functions, two new groups of fuzzy mathematical morphology (FMM) operators were proposed and applied to image processing, and they obtained better results than...
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| Vydané v: | Fractal and fractional Ročník 7; číslo 6; s. 465 |
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01.06.2023
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| Abstract | As special aggregation functions, overlap functions have been widely used in the soft computing field. In this work, with the aid of overlap functions, two new groups of fuzzy mathematical morphology (FMM) operators were proposed and applied to image processing, and they obtained better results than existing algorithms. First, based on overlap functions and structuring elements, the first group of new FMM operators (called OSFMM operators) was proposed, and their properties were systematically analyzed. With the implementation of OSFMM operators and the fuzzy C-means (FCM) algorithm, a new image edge extraction algorithm (called the OS-FCM algorithm) was proposed. Then, the second group of new FMM operators (called ORFMM operators) was proposed based on overlap functions and fuzzy relations. Another new image edge extraction algorithm (called OR-FCM algorithm) was proposed by using ORFMM operators and FCM algorithm. Finally, through the edge segmentation experiments of multiple standard images, the actual segmentation effects of the above-mentioned two algorithms and relevant algorithms were compared. The acquired results demonstrate that the image edge extraction algorithms proposed in this work can extract the complete edge of foreground objects on the basis of introducing the least noise. |
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| AbstractList | As special aggregation functions, overlap functions have been widely used in the soft computing field. In this work, with the aid of overlap functions, two new groups of fuzzy mathematical morphology (FMM) operators were proposed and applied to image processing, and they obtained better results than existing algorithms. First, based on overlap functions and structuring elements, the first group of new FMM operators (called OSFMM operators) was proposed, and their properties were systematically analyzed. With the implementation of OSFMM operators and the fuzzy C-means (FCM) algorithm, a new image edge extraction algorithm (called the OS-FCM algorithm) was proposed. Then, the second group of new FMM operators (called ORFMM operators) was proposed based on overlap functions and fuzzy relations. Another new image edge extraction algorithm (called OR-FCM algorithm) was proposed by using ORFMM operators and FCM algorithm. Finally, through the edge segmentation experiments of multiple standard images, the actual segmentation effects of the above-mentioned two algorithms and relevant algorithms were compared. The acquired results demonstrate that the image edge extraction algorithms proposed in this work can extract the complete edge of foreground objects on the basis of introducing the least noise. |
| Audience | Academic |
| Author | Liu, Hui Zhang, Xiaohong Li, Mengyuan |
| Author_xml | – sequence: 1 givenname: Xiaohong surname: Zhang fullname: Zhang, Xiaohong – sequence: 2 givenname: Mengyuan surname: Li fullname: Li, Mengyuan – sequence: 3 givenname: Hui surname: Liu fullname: Liu, Hui |
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| SubjectTerms | Algorithms fuzzy mathematical morphology Fuzzy sets Group theory Image acquisition image edge extraction Image processing Image segmentation Mathematical analysis Mathematical morphology Medical imaging equipment Morphology Operators (mathematics) overlap function Set theory Soft computing Video compression |
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