Generalized Quantification Function of Monogenic Phase Congruency
Edge detection is a technique in digital image processing that detects the contours of objects based on changes in brightness. Edges can be used to determine the size, orientation, and properties of the object of interest within an image. There are different techniques employed for edge detection, o...
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MDPI AG
2023-09-01
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| Series: | Mathematics |
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| Online Access: | https://www.mdpi.com/2227-7390/11/17/3795 |
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| author | Manuel G. Forero Carlos A. Jacanamejoy Maximiliano Machado Karla L. Penagos |
| author_facet | Manuel G. Forero Carlos A. Jacanamejoy Maximiliano Machado Karla L. Penagos |
| author_sort | Manuel G. Forero |
| collection | DOAJ |
| description | Edge detection is a technique in digital image processing that detects the contours of objects based on changes in brightness. Edges can be used to determine the size, orientation, and properties of the object of interest within an image. There are different techniques employed for edge detection, one of them being phase congruency, a recently developed but still relatively unknown technique due to its mathematical and computational complexity compared to more popular methods. Additionally, it requires the adjustment of a greater number of parameters than traditional techniques. Recently, a unique formulation was proposed for the mathematical description of phase congruency, leading to a better understanding of the technique. This formulation consists of three factors, including a quantification function, which, depending on its characteristics, allows for improved edge detection. However, a detailed study of the characteristics had not been conducted. Therefore, this article proposes the development of a generalized function for quantifying phase congruency, based on the family of functions that, according to a previous study, yielded the best results in edge detection. |
| first_indexed | 2024-03-10T23:17:58Z |
| format | Article |
| id | doaj.art-ee548f58d55f4a10ab9d82d9d9a5813c |
| institution | Directory Open Access Journal |
| issn | 2227-7390 |
| language | English |
| last_indexed | 2024-03-10T23:17:58Z |
| publishDate | 2023-09-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Mathematics |
| spelling | doaj.art-ee548f58d55f4a10ab9d82d9d9a5813c2023-11-19T08:32:15ZengMDPI AGMathematics2227-73902023-09-011117379510.3390/math11173795Generalized Quantification Function of Monogenic Phase CongruencyManuel G. Forero0Carlos A. Jacanamejoy1Maximiliano Machado2Karla L. Penagos3Professional School of Systems Engineering, Faculty of Engineering, Architecture and Urban Planning, Universidad Señor de Sipán, Chiclayo 14000, Lambayeque, PeruSemillero Lún, Grupo Naturatu, Faculty of Natural Sciences and Mathematics, Universidad de Ibagué, Ibagué 730002, ColombiaGrupo Naturatu, Faculty of Natural Sciences and Mathematics, Universidad de Ibagué, Ibagué 730002, ColombiaSemillero Lún, Grupo D+Tec, Faculty of Engineering, Universidad de Ibagué, Ibagué 730002, ColombiaEdge detection is a technique in digital image processing that detects the contours of objects based on changes in brightness. Edges can be used to determine the size, orientation, and properties of the object of interest within an image. There are different techniques employed for edge detection, one of them being phase congruency, a recently developed but still relatively unknown technique due to its mathematical and computational complexity compared to more popular methods. Additionally, it requires the adjustment of a greater number of parameters than traditional techniques. Recently, a unique formulation was proposed for the mathematical description of phase congruency, leading to a better understanding of the technique. This formulation consists of three factors, including a quantification function, which, depending on its characteristics, allows for improved edge detection. However, a detailed study of the characteristics had not been conducted. Therefore, this article proposes the development of a generalized function for quantifying phase congruency, based on the family of functions that, according to a previous study, yielded the best results in edge detection.https://www.mdpi.com/2227-7390/11/17/3795phase congruencymonogenic filtersedge detectionlocal energylog-Gabor filterFourier transform |
| spellingShingle | Manuel G. Forero Carlos A. Jacanamejoy Maximiliano Machado Karla L. Penagos Generalized Quantification Function of Monogenic Phase Congruency Mathematics phase congruency monogenic filters edge detection local energy log-Gabor filter Fourier transform |
| title | Generalized Quantification Function of Monogenic Phase Congruency |
| title_full | Generalized Quantification Function of Monogenic Phase Congruency |
| title_fullStr | Generalized Quantification Function of Monogenic Phase Congruency |
| title_full_unstemmed | Generalized Quantification Function of Monogenic Phase Congruency |
| title_short | Generalized Quantification Function of Monogenic Phase Congruency |
| title_sort | generalized quantification function of monogenic phase congruency |
| topic | phase congruency monogenic filters edge detection local energy log-Gabor filter Fourier transform |
| url | https://www.mdpi.com/2227-7390/11/17/3795 |
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