Research on Automatic Recognition Method of Artificial Ground Target Based on Improved HED
Automatic target recognition technology is an important research direction in the field of machine vision. Artificial ground targets, such as bridges, airports and houses, are mostly composed of straight lines. The ratio of geometric primitive lines to the triangle area formed by their combination i...
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-03-01
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| Series: | Applied Sciences |
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| Online Access: | https://www.mdpi.com/2076-3417/13/5/3163 |
| _version_ | 1797615719227064320 |
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| author | Wei Zhong Yueqiu Jiang Xin Zhang |
| author_facet | Wei Zhong Yueqiu Jiang Xin Zhang |
| author_sort | Wei Zhong |
| collection | DOAJ |
| description | Automatic target recognition technology is an important research direction in the field of machine vision. Artificial ground targets, such as bridges, airports and houses, are mostly composed of straight lines. The ratio of geometric primitive lines to the triangle area formed by their combination is used as the feature quantity to describe the group of lines, so as to characterize the artificial ground target. In view of the shortcomings of traditional edge detection methods, such as background suppression, non-prominent targets, missing positions, etc., this paper proposed an image edge detection method based on depth learning. By combining the traditional edge detection algorithm with the edge detection algorithm based on an improved HED network, the real-time target image edge detection was completed. An automatic target recognition method based on template matching was proposed. This method solved the problem of both homologous template matching and heterogeneous template matching, which has important theoretical value. First, the lines were combined to form the geometric primitives of the line group, and then the relationship of the lines in the group was determined by using the characteristic quantity of the line group. The best line group matching the target template was found in the image edge, and the homonymous points in the real-time image and the target template were calculated. The affine transformation matrix between the two images was obtained according to the homonymous points, and then the accurate position of the target in the real-time image was found. |
| first_indexed | 2024-03-11T07:30:39Z |
| format | Article |
| id | doaj.art-56589ac31313466b80a0e7edd6645296 |
| institution | Directory Open Access Journal |
| issn | 2076-3417 |
| language | English |
| last_indexed | 2024-03-11T07:30:39Z |
| publishDate | 2023-03-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj.art-56589ac31313466b80a0e7edd66452962023-11-17T07:20:06ZengMDPI AGApplied Sciences2076-34172023-03-01135316310.3390/app13053163Research on Automatic Recognition Method of Artificial Ground Target Based on Improved HEDWei Zhong0Yueqiu Jiang1Xin Zhang2Graduate School, Shenyang Ligong University, Shenyang 110159, ChinaSchool of Information Science and Engineering, Shenyang Ligong University, Shenyang 110159, ChinaSchool of Automobile and Traffic, Shenyang Ligong University, Shenyang 110159, ChinaAutomatic target recognition technology is an important research direction in the field of machine vision. Artificial ground targets, such as bridges, airports and houses, are mostly composed of straight lines. The ratio of geometric primitive lines to the triangle area formed by their combination is used as the feature quantity to describe the group of lines, so as to characterize the artificial ground target. In view of the shortcomings of traditional edge detection methods, such as background suppression, non-prominent targets, missing positions, etc., this paper proposed an image edge detection method based on depth learning. By combining the traditional edge detection algorithm with the edge detection algorithm based on an improved HED network, the real-time target image edge detection was completed. An automatic target recognition method based on template matching was proposed. This method solved the problem of both homologous template matching and heterogeneous template matching, which has important theoretical value. First, the lines were combined to form the geometric primitives of the line group, and then the relationship of the lines in the group was determined by using the characteristic quantity of the line group. The best line group matching the target template was found in the image edge, and the homonymous points in the real-time image and the target template were calculated. The affine transformation matrix between the two images was obtained according to the homonymous points, and then the accurate position of the target in the real-time image was found.https://www.mdpi.com/2076-3417/13/5/3163geometric primitivedeep learningautomatic target recognitionimprove HED network |
| spellingShingle | Wei Zhong Yueqiu Jiang Xin Zhang Research on Automatic Recognition Method of Artificial Ground Target Based on Improved HED Applied Sciences geometric primitive deep learning automatic target recognition improve HED network |
| title | Research on Automatic Recognition Method of Artificial Ground Target Based on Improved HED |
| title_full | Research on Automatic Recognition Method of Artificial Ground Target Based on Improved HED |
| title_fullStr | Research on Automatic Recognition Method of Artificial Ground Target Based on Improved HED |
| title_full_unstemmed | Research on Automatic Recognition Method of Artificial Ground Target Based on Improved HED |
| title_short | Research on Automatic Recognition Method of Artificial Ground Target Based on Improved HED |
| title_sort | research on automatic recognition method of artificial ground target based on improved hed |
| topic | geometric primitive deep learning automatic target recognition improve HED network |
| url | https://www.mdpi.com/2076-3417/13/5/3163 |
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