Edge Detection Method Driven by Knowledge-Based Neighborhood Rules
Edge detection is a fundamental process, and therefore there are still demands to improve its efficiency and computational complexity. This study proposes a knowledge-based edge detection method to meet this requirement by introducing a set of knowledge-based rules. The methodology to derive the ru...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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Taiwan Association of Engineering and Technology Innovation
2023-01-01
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| Series: | International Journal of Engineering and Technology Innovation |
| Subjects: | |
| Online Access: | https://ojs.imeti.org/index.php/IJETI/article/view/9710 |
| _version_ | 1797808609283801088 |
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| author | Yavuz Çapkan Halis Altun Can Bülent Fidan |
| author_facet | Yavuz Çapkan Halis Altun Can Bülent Fidan |
| author_sort | Yavuz Çapkan |
| collection | DOAJ |
| description |
Edge detection is a fundamental process, and therefore there are still demands to improve its efficiency and computational complexity. This study proposes a knowledge-based edge detection method to meet this requirement by introducing a set of knowledge-based rules. The methodology to derive the rules is based on the observed continuity properties and the neighborhood characteristics of the edge pixels, which are expressed as simple arithmetical operations to improve computational complexity. The results show that the method has an advantage over the gradient-based methods in terms of performance and computational load. It is appropriately four times faster than Canny method and shows superior performance compared to the gradient-based methods in general. Furthermore, the proposed method provides robustness to effectively identify edges at the corners. Due to its light computational requirement and inherent parallelization properties, the method would be also suitable for hardware implementation on field-programmable gate arrays (FPGA).
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| first_indexed | 2024-03-13T06:40:11Z |
| format | Article |
| id | doaj.art-64726b5a0bf74b8383ecbaced786af3e |
| institution | Directory Open Access Journal |
| issn | 2223-5329 2226-809X |
| language | English |
| last_indexed | 2024-03-13T06:40:11Z |
| publishDate | 2023-01-01 |
| publisher | Taiwan Association of Engineering and Technology Innovation |
| record_format | Article |
| series | International Journal of Engineering and Technology Innovation |
| spelling | doaj.art-64726b5a0bf74b8383ecbaced786af3e2023-06-08T18:07:11ZengTaiwan Association of Engineering and Technology InnovationInternational Journal of Engineering and Technology Innovation2223-53292226-809X2023-01-0113110.46604/ijeti.2023.9710Edge Detection Method Driven by Knowledge-Based Neighborhood RulesYavuz Çapkan0Halis Altun1Can Bülent Fidan2Department of Mechatronics Engineering, Yildiz Technical University, Istanbul, TurkeyDepartment of Software Engineering, Istanbul Health and Technology University, Istanbul, TurkeyDepartment of Mechatronics Engineering, Karabuk University, Karabuk, Turkey Edge detection is a fundamental process, and therefore there are still demands to improve its efficiency and computational complexity. This study proposes a knowledge-based edge detection method to meet this requirement by introducing a set of knowledge-based rules. The methodology to derive the rules is based on the observed continuity properties and the neighborhood characteristics of the edge pixels, which are expressed as simple arithmetical operations to improve computational complexity. The results show that the method has an advantage over the gradient-based methods in terms of performance and computational load. It is appropriately four times faster than Canny method and shows superior performance compared to the gradient-based methods in general. Furthermore, the proposed method provides robustness to effectively identify edges at the corners. Due to its light computational requirement and inherent parallelization properties, the method would be also suitable for hardware implementation on field-programmable gate arrays (FPGA). https://ojs.imeti.org/index.php/IJETI/article/view/9710image processingedge detectioncomputer visionimage analysis |
| spellingShingle | Yavuz Çapkan Halis Altun Can Bülent Fidan Edge Detection Method Driven by Knowledge-Based Neighborhood Rules International Journal of Engineering and Technology Innovation image processing edge detection computer vision image analysis |
| title | Edge Detection Method Driven by Knowledge-Based Neighborhood Rules |
| title_full | Edge Detection Method Driven by Knowledge-Based Neighborhood Rules |
| title_fullStr | Edge Detection Method Driven by Knowledge-Based Neighborhood Rules |
| title_full_unstemmed | Edge Detection Method Driven by Knowledge-Based Neighborhood Rules |
| title_short | Edge Detection Method Driven by Knowledge-Based Neighborhood Rules |
| title_sort | edge detection method driven by knowledge based neighborhood rules |
| topic | image processing edge detection computer vision image analysis |
| url | https://ojs.imeti.org/index.php/IJETI/article/view/9710 |
| work_keys_str_mv | AT yavuzcapkan edgedetectionmethoddrivenbyknowledgebasedneighborhoodrules AT halisaltun edgedetectionmethoddrivenbyknowledgebasedneighborhoodrules AT canbulentfidan edgedetectionmethoddrivenbyknowledgebasedneighborhoodrules |