Color Image Edge Detection Method Based on the Improved Whale Optimization Algorithm
A high level of computation is required for edge detection in color images captured by unmanned aerial vehicles (UAVs) to address issues, such as noise, distortion, and information loss. Thus, an edge detection method for UAV-captured color images based on the improved whale optimization algorithm (...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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IEEE
2023-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/10016728/ |
| _version_ | 1797945082146455552 |
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| author | Dujin Liu Shiji Zhou Rong Shen Xuegang Luo |
| author_facet | Dujin Liu Shiji Zhou Rong Shen Xuegang Luo |
| author_sort | Dujin Liu |
| collection | DOAJ |
| description | A high level of computation is required for edge detection in color images captured by unmanned aerial vehicles (UAVs) to address issues, such as noise, distortion, and information loss. Thus, an edge detection method for UAV-captured color images based on the improved whale optimization algorithm (WOA) is proposed in this study. In this method, the color image pixels are represented by quaternions, and the global random position variables and information exchange mechanism are introduced into the random walk foraging formula of the WOA. Further, a random disturbance factor is also introduced into the predator-prey formula of the spiral bubble net. The proposed improved WOA is then used to obtain the preliminary edge of the UAV-captured color image. An edge-point classification method using the radius of the shortest distance between the whale and the current global optimum in each iteration is presented to enhance a preliminary edge. The experimental results show that the proposed edge detection method has the advantages of strong denoising, fast speed, and good quality. |
| first_indexed | 2024-04-10T20:49:38Z |
| format | Article |
| id | doaj.art-e5cfc13db6434761b7806ba629c1ff93 |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-04-10T20:49:38Z |
| publishDate | 2023-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-e5cfc13db6434761b7806ba629c1ff932023-01-24T00:00:41ZengIEEEIEEE Access2169-35362023-01-01115981598910.1109/ACCESS.2023.323676110016728Color Image Edge Detection Method Based on the Improved Whale Optimization AlgorithmDujin Liu0https://orcid.org/0000-0001-8822-6722Shiji Zhou1Rong Shen2Xuegang Luo3School of Intelligent Manufacturing, Sichuan University of Arts and Science, Dazhou, ChinaSchool of Intelligent Manufacturing, Sichuan University of Arts and Science, Dazhou, ChinaSchool of Intelligent Manufacturing, Sichuan University of Arts and Science, Dazhou, ChinaSchool of Mathematics and Computer, Panzhihua University, Panzhihua, ChinaA high level of computation is required for edge detection in color images captured by unmanned aerial vehicles (UAVs) to address issues, such as noise, distortion, and information loss. Thus, an edge detection method for UAV-captured color images based on the improved whale optimization algorithm (WOA) is proposed in this study. In this method, the color image pixels are represented by quaternions, and the global random position variables and information exchange mechanism are introduced into the random walk foraging formula of the WOA. Further, a random disturbance factor is also introduced into the predator-prey formula of the spiral bubble net. The proposed improved WOA is then used to obtain the preliminary edge of the UAV-captured color image. An edge-point classification method using the radius of the shortest distance between the whale and the current global optimum in each iteration is presented to enhance a preliminary edge. The experimental results show that the proposed edge detection method has the advantages of strong denoising, fast speed, and good quality.https://ieeexplore.ieee.org/document/10016728/Classification and purificationedge detectionquaternionunmanned aerial vehicle (UAV)whale optimization algorithm (WOA) |
| spellingShingle | Dujin Liu Shiji Zhou Rong Shen Xuegang Luo Color Image Edge Detection Method Based on the Improved Whale Optimization Algorithm IEEE Access Classification and purification edge detection quaternion unmanned aerial vehicle (UAV) whale optimization algorithm (WOA) |
| title | Color Image Edge Detection Method Based on the Improved Whale Optimization Algorithm |
| title_full | Color Image Edge Detection Method Based on the Improved Whale Optimization Algorithm |
| title_fullStr | Color Image Edge Detection Method Based on the Improved Whale Optimization Algorithm |
| title_full_unstemmed | Color Image Edge Detection Method Based on the Improved Whale Optimization Algorithm |
| title_short | Color Image Edge Detection Method Based on the Improved Whale Optimization Algorithm |
| title_sort | color image edge detection method based on the improved whale optimization algorithm |
| topic | Classification and purification edge detection quaternion unmanned aerial vehicle (UAV) whale optimization algorithm (WOA) |
| url | https://ieeexplore.ieee.org/document/10016728/ |
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