Defect Detection Image Processing Technology Based on Swarm Intelligence Optimization Algorithm
The swarm intelligence optimization algorithm has obtained good results in practical application in the field of image processing with defect detection, and it has become the focus and hot spot of attention and research in the field of image processing. In this paper, the application of ALO as the r...
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| Vydáno v: | Journal of physics. Conference series Ročník 2400; číslo 1; s. 12031 - 12037 |
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| Hlavní autoři: | , |
| Médium: | Journal Article |
| Jazyk: | angličtina |
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Bristol
IOP Publishing
01.12.2022
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| ISSN: | 1742-6588, 1742-6596 |
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| Abstract | The swarm intelligence optimization algorithm has obtained good results in practical application in the field of image processing with defect detection, and it has become the focus and hot spot of attention and research in the field of image processing. In this paper, the application of ALO as the representative of the relevant swarm intelligence optimization algorithm is studied to address the problems and shortcomings of image processing technology in the field of object defect detection. By extracting typical defect detection image samples, the effect of the application of the algorithm in sample processing is systematically studied. In addition, the introduction of perturbation strategy and inertia weights in ALO effectively improves the search performance of the algorithm. Finally, this paper analyzes the performance comparison between the commonly used defect detection image processing techniques and the algorithm in this paper by establishing comparative verification experiments. The experimental results show that the image processing strategy constructed in this paper has significant application advantages in the dimensions of image enhancement and image processing applicability. |
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| AbstractList | The swarm intelligence optimization algorithm has obtained good results in practical application in the field of image processing with defect detection, and it has become the focus and hot spot of attention and research in the field of image processing. In this paper, the application of ALO as the representative of the relevant swarm intelligence optimization algorithm is studied to address the problems and shortcomings of image processing technology in the field of object defect detection. By extracting typical defect detection image samples, the effect of the application of the algorithm in sample processing is systematically studied. In addition, the introduction of perturbation strategy and inertia weights in ALO effectively improves the search performance of the algorithm. Finally, this paper analyzes the performance comparison between the commonly used defect detection image processing techniques and the algorithm in this paper by establishing comparative verification experiments. The experimental results show that the image processing strategy constructed in this paper has significant application advantages in the dimensions of image enhancement and image processing applicability. |
| Author | Zhu, Shan Zhang, Kui |
| Author_xml | – sequence: 1 givenname: Kui surname: Zhang fullname: Zhang, Kui organization: Shanghai Normal University Tianhua College , China – sequence: 2 givenname: Shan surname: Zhu fullname: Zhu, Shan organization: Shanghai Normal University Tianhua College , China |
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| Cites_doi | 10.1016/j.inffus.2012.01.007 10.1016/j.chaos.2009.01.012 10.1016/j.chemolab.2017.11.018 10.1007/s40031-017-0296-2 10.1016/j.ijhydene.2019.04.039 |
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| DOI | 10.1088/1742-6596/2400/1/012031 |
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| SubjectTerms | Algorithms Defects Image enhancement Image processing Optimization Optimization algorithms Perturbation Physics Swarm intelligence |
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