A Survey on Various Edge Detection Techniques in Image Processing and Applied Disease Detection
This paper surveys various edge detection techniques in image processing, focusing on their applicability to disease detection. Many researchers encompass studies conducted in the context of various crops and fruits, shedding light on their effectiveness and adaptability. However, the more techniqu...
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| Format: | Article |
| Language: | English |
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Faculty of Computer and Mathematical Sciences, Universiti Teknologi MARA Perlis
2024-09-01
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| Series: | Journal of Computing Research and Innovation |
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| Online Access: | https://www.conferencehunter.com/index.php/jcrinn/article/view/415 |
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| author | Wan Muhammad Rahimi Wan Fadzli Ahmad Yusri Dak Tajul Rosli Razak |
| author_facet | Wan Muhammad Rahimi Wan Fadzli Ahmad Yusri Dak Tajul Rosli Razak |
| author_sort | Wan Muhammad Rahimi Wan Fadzli |
| collection | DOAJ |
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This paper surveys various edge detection techniques in image processing, focusing on their applicability to disease detection. Many researchers encompass studies conducted in the context of various crops and fruits, shedding light on their effectiveness and adaptability. However, the more techniques are used and improved, less comparison has been made between them to look further at their challenges, such as noise sensitivity, scale variability, edge linking, and real-world variability. Also, the study will systematically survey and analyze literature on the ability of edge detection, including classical methods like Robert, Sobel, Prewitt, and Canny, as well as more advanced techniques such as gradient-based and Gaussian-based. This research aims to comprehensively understand the strengths and limitations of different edge detection techniques and can be used as a reference point for selecting and enhancing novel techniques in image processing. Overview, this paper makes a substantial contribution to the field by addressing both traditional edge detection in image processing and applied disease detection. It serves as a comprehensive guide, offering insights, practical advice, and a consolidated view of current research trends, and highlights the potential of edge detection in contributing to advancements in disease detection methodologies making it a valuable resource for researchers and practitioners.
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| format | Article |
| id | doaj-art-7c813752e8a340a78d54583a3011ef21 |
| institution | DOAJ |
| issn | 2600-8793 |
| language | English |
| publishDate | 2024-09-01 |
| publisher | Faculty of Computer and Mathematical Sciences, Universiti Teknologi MARA Perlis |
| record_format | Article |
| series | Journal of Computing Research and Innovation |
| spelling | doaj-art-7c813752e8a340a78d54583a3011ef212025-08-20T02:49:53ZengFaculty of Computer and Mathematical Sciences, Universiti Teknologi MARA PerlisJournal of Computing Research and Innovation2600-87932024-09-019210.24191/jcrinn.v9i2.415A Survey on Various Edge Detection Techniques in Image Processing and Applied Disease Detection Wan Muhammad Rahimi Wan Fadzli0Ahmad Yusri Dak1Tajul Rosli Razak2College of Computing, Informatics and Mathematics, Universiti Teknologi MARA Perlis Branch, Arau Campus, Arau, Perlis. MALAYSIACollege of Computing, Informatics and Mathematics, Universiti Teknologi MARA Perlis Branch, Arau Campus, Arau, Perlis. MALAYSIACollege of Computing, Informatics and Mathematics, Universiti Teknologi MARA, Shah Alam, Selangor. MALAYSIA This paper surveys various edge detection techniques in image processing, focusing on their applicability to disease detection. Many researchers encompass studies conducted in the context of various crops and fruits, shedding light on their effectiveness and adaptability. However, the more techniques are used and improved, less comparison has been made between them to look further at their challenges, such as noise sensitivity, scale variability, edge linking, and real-world variability. Also, the study will systematically survey and analyze literature on the ability of edge detection, including classical methods like Robert, Sobel, Prewitt, and Canny, as well as more advanced techniques such as gradient-based and Gaussian-based. This research aims to comprehensively understand the strengths and limitations of different edge detection techniques and can be used as a reference point for selecting and enhancing novel techniques in image processing. Overview, this paper makes a substantial contribution to the field by addressing both traditional edge detection in image processing and applied disease detection. It serves as a comprehensive guide, offering insights, practical advice, and a consolidated view of current research trends, and highlights the potential of edge detection in contributing to advancements in disease detection methodologies making it a valuable resource for researchers and practitioners. https://www.conferencehunter.com/index.php/jcrinn/article/view/415Edge detectionImage ProcessingGradient-basedEdge detectorCanny |
| spellingShingle | Wan Muhammad Rahimi Wan Fadzli Ahmad Yusri Dak Tajul Rosli Razak A Survey on Various Edge Detection Techniques in Image Processing and Applied Disease Detection Journal of Computing Research and Innovation Edge detection Image Processing Gradient-based Edge detector Canny |
| title | A Survey on Various Edge Detection Techniques in Image Processing and Applied Disease Detection |
| title_full | A Survey on Various Edge Detection Techniques in Image Processing and Applied Disease Detection |
| title_fullStr | A Survey on Various Edge Detection Techniques in Image Processing and Applied Disease Detection |
| title_full_unstemmed | A Survey on Various Edge Detection Techniques in Image Processing and Applied Disease Detection |
| title_short | A Survey on Various Edge Detection Techniques in Image Processing and Applied Disease Detection |
| title_sort | survey on various edge detection techniques in image processing and applied disease detection |
| topic | Edge detection Image Processing Gradient-based Edge detector Canny |
| url | https://www.conferencehunter.com/index.php/jcrinn/article/view/415 |
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