Ellipse Detection with Applications of Convolutional Neural Network in Industrial Images
Ellipse detection has a very wide range of applications in the field of industrial production, especially in the geometric detection of metallurgical hinge pins. However, the factors in industrial images, such as small object size and incomplete ellipse in the image boundary, bring challenges to ell...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-08-01
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| Series: | Electronics |
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| Online Access: | https://www.mdpi.com/2079-9292/12/16/3431 |
| _version_ | 1797584894810914816 |
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| author | Kang Liu Yonggang Lu Rubing Bai Kun Xu Tao Peng Yichun Tai Zhijiang Zhang |
| author_facet | Kang Liu Yonggang Lu Rubing Bai Kun Xu Tao Peng Yichun Tai Zhijiang Zhang |
| author_sort | Kang Liu |
| collection | DOAJ |
| description | Ellipse detection has a very wide range of applications in the field of industrial production, especially in the geometric detection of metallurgical hinge pins. However, the factors in industrial images, such as small object size and incomplete ellipse in the image boundary, bring challenges to ellipse detection, which cannot be solved by existing methods. This paper proposes a method for ellipse detection in industrial images, which utilizes the extended proposal operation to prevent the loss of ellipse rotation angle features during ellipse regression. Moreover, the Gaussian angle distance conforming to the ellipse axioms is adopted and combined with smooth <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msub><mi>L</mi><mn>1</mn></msub></semantics></math></inline-formula> loss as the ellipse regression loss function to enhance the prediction accuracy of the ellipse rotation angle. The effectiveness of the proposed method is demonstrated on the hinge pins dataset, with experiment results showing an AP<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msub><mrow></mrow><mo>*</mo></msub></semantics></math></inline-formula> of 80.93% and indicating superior detection performance compared to other methods. It is thus suitable for engineering applications and can provide visual guidance for the precise measurement of ellipse-like mechanical parts. |
| first_indexed | 2024-03-10T23:59:10Z |
| format | Article |
| id | doaj.art-59fdd1396c344ae383f518f8548d6257 |
| institution | Directory Open Access Journal |
| issn | 2079-9292 |
| language | English |
| last_indexed | 2024-03-10T23:59:10Z |
| publishDate | 2023-08-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Electronics |
| spelling | doaj.art-59fdd1396c344ae383f518f8548d62572023-11-19T00:53:31ZengMDPI AGElectronics2079-92922023-08-011216343110.3390/electronics12163431Ellipse Detection with Applications of Convolutional Neural Network in Industrial ImagesKang Liu0Yonggang Lu1Rubing Bai2Kun Xu3Tao Peng4Yichun Tai5Zhijiang Zhang6School of Communication and Information Engineering, Shanghai University, Shanghai 201900, ChinaMetallurgical Baosteel Technical Services Co., Ltd., Shanghai 201900, ChinaMetallurgical Baosteel Technical Services Co., Ltd., Shanghai 201900, ChinaMetallurgical Baosteel Technical Services Co., Ltd., Shanghai 201900, ChinaSchool of Communication and Information Engineering, Shanghai University, Shanghai 201900, ChinaSchool of Communication and Information Engineering, Shanghai University, Shanghai 201900, ChinaSchool of Communication and Information Engineering, Shanghai University, Shanghai 201900, ChinaEllipse detection has a very wide range of applications in the field of industrial production, especially in the geometric detection of metallurgical hinge pins. However, the factors in industrial images, such as small object size and incomplete ellipse in the image boundary, bring challenges to ellipse detection, which cannot be solved by existing methods. This paper proposes a method for ellipse detection in industrial images, which utilizes the extended proposal operation to prevent the loss of ellipse rotation angle features during ellipse regression. Moreover, the Gaussian angle distance conforming to the ellipse axioms is adopted and combined with smooth <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msub><mi>L</mi><mn>1</mn></msub></semantics></math></inline-formula> loss as the ellipse regression loss function to enhance the prediction accuracy of the ellipse rotation angle. The effectiveness of the proposed method is demonstrated on the hinge pins dataset, with experiment results showing an AP<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msub><mrow></mrow><mo>*</mo></msub></semantics></math></inline-formula> of 80.93% and indicating superior detection performance compared to other methods. It is thus suitable for engineering applications and can provide visual guidance for the precise measurement of ellipse-like mechanical parts.https://www.mdpi.com/2079-9292/12/16/3431ellipse detectionconvolutional neural networkhinge pinsproposal extensionGaussian angle distance |
| spellingShingle | Kang Liu Yonggang Lu Rubing Bai Kun Xu Tao Peng Yichun Tai Zhijiang Zhang Ellipse Detection with Applications of Convolutional Neural Network in Industrial Images Electronics ellipse detection convolutional neural network hinge pins proposal extension Gaussian angle distance |
| title | Ellipse Detection with Applications of Convolutional Neural Network in Industrial Images |
| title_full | Ellipse Detection with Applications of Convolutional Neural Network in Industrial Images |
| title_fullStr | Ellipse Detection with Applications of Convolutional Neural Network in Industrial Images |
| title_full_unstemmed | Ellipse Detection with Applications of Convolutional Neural Network in Industrial Images |
| title_short | Ellipse Detection with Applications of Convolutional Neural Network in Industrial Images |
| title_sort | ellipse detection with applications of convolutional neural network in industrial images |
| topic | ellipse detection convolutional neural network hinge pins proposal extension Gaussian angle distance |
| url | https://www.mdpi.com/2079-9292/12/16/3431 |
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