An Edge Detection Method Based on Local Gradient Estimation: Application to High-Temperature Metallic Droplet Images
Edge detection is a fundamental step in many computer vision systems, particularly in image segmentation and feature detection. There are a lot of algorithms for detecting edges of objects in images. This paper proposes a method based on local gradient estimation to detect metallic droplet image edg...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2022-07-01
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| Series: | Applied Sciences |
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| Online Access: | https://www.mdpi.com/2076-3417/12/14/6976 |
| _version_ | 1797407631057354752 |
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| author | Ranya Al Darwich Laurent Babout Krzysztof Strzecha |
| author_facet | Ranya Al Darwich Laurent Babout Krzysztof Strzecha |
| author_sort | Ranya Al Darwich |
| collection | DOAJ |
| description | Edge detection is a fundamental step in many computer vision systems, particularly in image segmentation and feature detection. There are a lot of algorithms for detecting edges of objects in images. This paper proposes a method based on local gradient estimation to detect metallic droplet image edges and compare the results to a contour line obtained from the active contour model of the same images, and to results from crowdsourcing to identify droplet edges at specific points. The studied images were taken at high temperatures, which makes the segmentation process particularly difficult. The comparison between the three methods shows that the proposed method is more accurate than the active contour method, especially at the point of contact between the droplet and the base. It is also shown that the reliability of the data from the crowdsourcing is as good as the edge points obtained from the local gradient estimation method. |
| first_indexed | 2024-03-09T03:45:15Z |
| format | Article |
| id | doaj.art-4a4739389e3447d4bf54c386e4efe93d |
| institution | Directory Open Access Journal |
| issn | 2076-3417 |
| language | English |
| last_indexed | 2024-03-09T03:45:15Z |
| publishDate | 2022-07-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj.art-4a4739389e3447d4bf54c386e4efe93d2023-12-03T14:35:39ZengMDPI AGApplied Sciences2076-34172022-07-011214697610.3390/app12146976An Edge Detection Method Based on Local Gradient Estimation: Application to High-Temperature Metallic Droplet ImagesRanya Al Darwich0Laurent Babout1Krzysztof Strzecha2Institute of Applied Computer Science, Łódź University of Technology, 90-537 Łódź, PolandInstitute of Applied Computer Science, Łódź University of Technology, 90-537 Łódź, PolandInstitute of Applied Computer Science, Łódź University of Technology, 90-537 Łódź, PolandEdge detection is a fundamental step in many computer vision systems, particularly in image segmentation and feature detection. There are a lot of algorithms for detecting edges of objects in images. This paper proposes a method based on local gradient estimation to detect metallic droplet image edges and compare the results to a contour line obtained from the active contour model of the same images, and to results from crowdsourcing to identify droplet edges at specific points. The studied images were taken at high temperatures, which makes the segmentation process particularly difficult. The comparison between the three methods shows that the proposed method is more accurate than the active contour method, especially at the point of contact between the droplet and the base. It is also shown that the reliability of the data from the crowdsourcing is as good as the edge points obtained from the local gradient estimation method.https://www.mdpi.com/2076-3417/12/14/6976edge detectionactive contourgradient-based edge detectioncrowdsourcing |
| spellingShingle | Ranya Al Darwich Laurent Babout Krzysztof Strzecha An Edge Detection Method Based on Local Gradient Estimation: Application to High-Temperature Metallic Droplet Images Applied Sciences edge detection active contour gradient-based edge detection crowdsourcing |
| title | An Edge Detection Method Based on Local Gradient Estimation: Application to High-Temperature Metallic Droplet Images |
| title_full | An Edge Detection Method Based on Local Gradient Estimation: Application to High-Temperature Metallic Droplet Images |
| title_fullStr | An Edge Detection Method Based on Local Gradient Estimation: Application to High-Temperature Metallic Droplet Images |
| title_full_unstemmed | An Edge Detection Method Based on Local Gradient Estimation: Application to High-Temperature Metallic Droplet Images |
| title_short | An Edge Detection Method Based on Local Gradient Estimation: Application to High-Temperature Metallic Droplet Images |
| title_sort | edge detection method based on local gradient estimation application to high temperature metallic droplet images |
| topic | edge detection active contour gradient-based edge detection crowdsourcing |
| url | https://www.mdpi.com/2076-3417/12/14/6976 |
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