General Type-2 Fuzzy Sugeno Integral for Edge Detection
A type-2 fuzzy edge detection method is presented in this paper. The general process consists of first obtaining the image gradients in the four directions—horizontal, vertical, and the two diagonals—and this technique is known as the morphological gradient. After that, the gener...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2019-08-01
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| Series: | Journal of Imaging |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2313-433X/5/8/71 |
| _version_ | 1818060090703347712 |
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| author | Gabriela E. Martínez Claudia I. Gonzalez Olivia Mendoza Patricia Melin |
| author_facet | Gabriela E. Martínez Claudia I. Gonzalez Olivia Mendoza Patricia Melin |
| author_sort | Gabriela E. Martínez |
| collection | DOAJ |
| description | A type-2 fuzzy edge detection method is presented in this paper. The general process consists of first obtaining the image gradients in the four directions—horizontal, vertical, and the two diagonals—and this technique is known as the morphological gradient. After that, the general type-2 fuzzy Sugeno integral (GT2 FSI) is used to integrate the four image gradients. In this second step, the GT2 FSI establishes criteria to determine at which level the obtained image gradient belongs to an edge during the process; this is calculated assigning different general type-2 fuzzy densities, and these fuzzy gradients are aggregated using the meet and join operators. The gradient integration using the GT2 FSI provides a methodology for achieving more robust edge detection, even more if we are working with blurry images. The experimental evaluations are performed on synthetic and real images, and the accuracy is quantified using Pratt’s Figure of Merit. The results values demonstrate that the proposed edge detection method outperforms other existing algorithms. |
| first_indexed | 2024-12-10T13:26:54Z |
| format | Article |
| id | doaj.art-7e09269f3d184d16a60e1dc12f345349 |
| institution | Directory Open Access Journal |
| issn | 2313-433X |
| language | English |
| last_indexed | 2024-12-10T13:26:54Z |
| publishDate | 2019-08-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Journal of Imaging |
| spelling | doaj.art-7e09269f3d184d16a60e1dc12f3453492022-12-22T01:47:07ZengMDPI AGJournal of Imaging2313-433X2019-08-01587110.3390/jimaging5080071jimaging5080071General Type-2 Fuzzy Sugeno Integral for Edge DetectionGabriela E. Martínez0Claudia I. Gonzalez1Olivia Mendoza2Patricia Melin3Division of Graduate Studies and Research, Tijuana Institute of Technology, Tijuana 22414, MexicoDivision of Graduate Studies and Research, Tijuana Institute of Technology, Tijuana 22414, MexicoSchool of Engineering, Autonomous University of Baja California, Tijuana 22390, MexicoDivision of Graduate Studies and Research, Tijuana Institute of Technology, Tijuana 22414, MexicoA type-2 fuzzy edge detection method is presented in this paper. The general process consists of first obtaining the image gradients in the four directions—horizontal, vertical, and the two diagonals—and this technique is known as the morphological gradient. After that, the general type-2 fuzzy Sugeno integral (GT2 FSI) is used to integrate the four image gradients. In this second step, the GT2 FSI establishes criteria to determine at which level the obtained image gradient belongs to an edge during the process; this is calculated assigning different general type-2 fuzzy densities, and these fuzzy gradients are aggregated using the meet and join operators. The gradient integration using the GT2 FSI provides a methodology for achieving more robust edge detection, even more if we are working with blurry images. The experimental evaluations are performed on synthetic and real images, and the accuracy is quantified using Pratt’s Figure of Merit. The results values demonstrate that the proposed edge detection method outperforms other existing algorithms.https://www.mdpi.com/2313-433X/5/8/71Sugeno integralfuzzy edge detectiongeneral type-2 fuzzy sets |
| spellingShingle | Gabriela E. Martínez Claudia I. Gonzalez Olivia Mendoza Patricia Melin General Type-2 Fuzzy Sugeno Integral for Edge Detection Journal of Imaging Sugeno integral fuzzy edge detection general type-2 fuzzy sets |
| title | General Type-2 Fuzzy Sugeno Integral for Edge Detection |
| title_full | General Type-2 Fuzzy Sugeno Integral for Edge Detection |
| title_fullStr | General Type-2 Fuzzy Sugeno Integral for Edge Detection |
| title_full_unstemmed | General Type-2 Fuzzy Sugeno Integral for Edge Detection |
| title_short | General Type-2 Fuzzy Sugeno Integral for Edge Detection |
| title_sort | general type 2 fuzzy sugeno integral for edge detection |
| topic | Sugeno integral fuzzy edge detection general type-2 fuzzy sets |
| url | https://www.mdpi.com/2313-433X/5/8/71 |
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