Magnesium Ingot Stacking Segmentation Algorithm for Industrial Robot Based on the Correction of Image Overexposure Area
This paper proposes an adaptive threshold segmentation algorithm for the magnesium ingot stack based on image overexposure area correction (ATSIOAC), which solves the problem of mirror reflection on the surface of magnesium alloy ingots caused by external ambient light and auxiliary light sources. F...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-07-01
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| Series: | Sensors |
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| Online Access: | https://www.mdpi.com/1424-8220/23/15/6809 |
| _version_ | 1797586045522411520 |
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| author | Qiguang Li Huazheng Zheng Wensheng Wang Chenggang Li |
| author_facet | Qiguang Li Huazheng Zheng Wensheng Wang Chenggang Li |
| author_sort | Qiguang Li |
| collection | DOAJ |
| description | This paper proposes an adaptive threshold segmentation algorithm for the magnesium ingot stack based on image overexposure area correction (ATSIOAC), which solves the problem of mirror reflection on the surface of magnesium alloy ingots caused by external ambient light and auxiliary light sources. Firstly, considering the brightness and chromaticity information of the mapped image, we divide the exposure probability threshold into weak exposure and strong exposure regions. Secondly, the saturation difference between the magnesium ingot region and the background region is used to obtain a mask for the magnesium ingot region to eliminate interference from the image background. Then, the RGB average of adjacent pixels in the overexposed area is used as a reference to correct the colors of the strongly exposed and weakly exposed areas, respectively. Furthermore, in order to smoothly fuse the two corrected images, pixel weighted average (WA) is applied. Finally, the magnesium ingot sorting experimental device was constructed and the corrected top surface image of the ingot pile was segmented through ATSIOAC. The experimental results show that the overexposed area detection and correction algorithm proposed in this paper can effectively correct the color information in the overexposed area, and when segmenting ingot images, complete segmentation results of the top surface of the ingot pile can be obtained, effectively improving the accuracy of magnesium alloy ingot segmentation. The segmentation algorithm achieves a segmentation accuracy of 94.38%. |
| first_indexed | 2024-03-11T00:16:44Z |
| format | Article |
| id | doaj.art-ae78063e49534fffb6f422deec682835 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-11T00:16:44Z |
| publishDate | 2023-07-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-ae78063e49534fffb6f422deec6828352023-11-18T23:34:46ZengMDPI AGSensors1424-82202023-07-012315680910.3390/s23156809Magnesium Ingot Stacking Segmentation Algorithm for Industrial Robot Based on the Correction of Image Overexposure AreaQiguang Li0Huazheng Zheng1Wensheng Wang2Chenggang Li3School of Mechanical and Electrical Engineering, Beijing Information Science and Technology University, Beijing 100192, ChinaSchool of Mechanical and Electrical Engineering, Beijing Information Science and Technology University, Beijing 100192, ChinaSchool of Mechanical and Electrical Engineering, Beijing Information Science and Technology University, Beijing 100192, ChinaJiaxing Worldia Diamond Tools Co., Ltd., Jiaxing 314031, ChinaThis paper proposes an adaptive threshold segmentation algorithm for the magnesium ingot stack based on image overexposure area correction (ATSIOAC), which solves the problem of mirror reflection on the surface of magnesium alloy ingots caused by external ambient light and auxiliary light sources. Firstly, considering the brightness and chromaticity information of the mapped image, we divide the exposure probability threshold into weak exposure and strong exposure regions. Secondly, the saturation difference between the magnesium ingot region and the background region is used to obtain a mask for the magnesium ingot region to eliminate interference from the image background. Then, the RGB average of adjacent pixels in the overexposed area is used as a reference to correct the colors of the strongly exposed and weakly exposed areas, respectively. Furthermore, in order to smoothly fuse the two corrected images, pixel weighted average (WA) is applied. Finally, the magnesium ingot sorting experimental device was constructed and the corrected top surface image of the ingot pile was segmented through ATSIOAC. The experimental results show that the overexposed area detection and correction algorithm proposed in this paper can effectively correct the color information in the overexposed area, and when segmenting ingot images, complete segmentation results of the top surface of the ingot pile can be obtained, effectively improving the accuracy of magnesium alloy ingot segmentation. The segmentation algorithm achieves a segmentation accuracy of 94.38%.https://www.mdpi.com/1424-8220/23/15/6809magnesium ingot sortingthe high reflection of magnesium ingotexposure correctionmagnesium ingot segmentation |
| spellingShingle | Qiguang Li Huazheng Zheng Wensheng Wang Chenggang Li Magnesium Ingot Stacking Segmentation Algorithm for Industrial Robot Based on the Correction of Image Overexposure Area Sensors magnesium ingot sorting the high reflection of magnesium ingot exposure correction magnesium ingot segmentation |
| title | Magnesium Ingot Stacking Segmentation Algorithm for Industrial Robot Based on the Correction of Image Overexposure Area |
| title_full | Magnesium Ingot Stacking Segmentation Algorithm for Industrial Robot Based on the Correction of Image Overexposure Area |
| title_fullStr | Magnesium Ingot Stacking Segmentation Algorithm for Industrial Robot Based on the Correction of Image Overexposure Area |
| title_full_unstemmed | Magnesium Ingot Stacking Segmentation Algorithm for Industrial Robot Based on the Correction of Image Overexposure Area |
| title_short | Magnesium Ingot Stacking Segmentation Algorithm for Industrial Robot Based on the Correction of Image Overexposure Area |
| title_sort | magnesium ingot stacking segmentation algorithm for industrial robot based on the correction of image overexposure area |
| topic | magnesium ingot sorting the high reflection of magnesium ingot exposure correction magnesium ingot segmentation |
| url | https://www.mdpi.com/1424-8220/23/15/6809 |
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