Automatic end-to-end veneer grading system based on machine vision Article Swipe
Fengying Ma
,
Jiyin Zhang
,
Peng Ji
·
YOU?
·
· 2021
· Open Access
·
· DOI: https://doi.org/10.1088/1742-6596/1961/1/012029
YOU?
·
· 2021
· Open Access
·
· DOI: https://doi.org/10.1088/1742-6596/1961/1/012029
In order to realize automatic grading of veneers of different quality during the processing of veneer veneers, an end-to-end veneer automatic grading system based on YOLOV3 was designed. Using YOLOV3 network as the defect detection model, self-made veneer defect data set for model training. Firstly, the system obtains the veneer surface image; then the trained model detects the obtained veneer surface image, identifies scars and cavities in the surface defects, and marks the scars and cavities with rectangular boxes respectively; finally, the quality level of the veneer is determined according to the characteristic information of the detected scars and holes, and the level signal is transmitted to the PLC system to drive the grading actuator for grading. Experiments show that the end-to-end veneer automatic grading system based on machine vision can effectively carry out the automatic veneer grading, which is helpful to realize the intelligent and automated production of veneer processing and improve work efficiency.
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- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1088/1742-6596/1961/1/012029
- OA Status
- diamond
- Cited By
- 1
- References
- 5
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- OpenAlex ID
- https://openalex.org/W3181658860
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W3181658860Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1088/1742-6596/1961/1/012029Digital Object Identifier
- Title
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Automatic end-to-end veneer grading system based on machine visionWork title
- Type
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2021Year of publication
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2021-07-01Full publication date if available
- Authors
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Fengying Ma, Jiyin Zhang, Peng JiList of authors in order
- Landing page
-
https://doi.org/10.1088/1742-6596/1961/1/012029Publisher landing page
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YesWhether a free full text is available
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diamondOpen access status per OpenAlex
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https://doi.org/10.1088/1742-6596/1961/1/012029Direct OA link when available
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Veneer, Grading (engineering), Computer science, Artificial intelligence, Computer vision, Image processing, Engineering drawing, Engineering, Materials science, Image (mathematics), Composite material, Civil engineeringTop concepts (fields/topics) attached by OpenAlex
- Cited by
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1Total citation count in OpenAlex
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2023: 1Per-year citation counts (last 5 years)
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5Number of works referenced by this work
- Related works (count)
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.quality | 11, 83 |
| abstract_inverted_index.realize | 4, 143 |
| abstract_inverted_index.surface | 51, 61, 69 |
| abstract_inverted_index.trained | 55 |
| abstract_inverted_index.veneers | 8 |
| abstract_inverted_index.Abstract | 0 |
| abstract_inverted_index.Firstly, | 45 |
| abstract_inverted_index.actuator | 115 |
| abstract_inverted_index.cavities | 66, 76 |
| abstract_inverted_index.defects, | 70 |
| abstract_inverted_index.detected | 97 |
| abstract_inverted_index.finally, | 81 |
| abstract_inverted_index.grading, | 138 |
| abstract_inverted_index.grading. | 117 |
| abstract_inverted_index.obtained | 59 |
| abstract_inverted_index.veneers, | 17 |
| abstract_inverted_index.according | 90 |
| abstract_inverted_index.automated | 147 |
| abstract_inverted_index.automatic | 5, 21, 124, 136 |
| abstract_inverted_index.designed. | 28 |
| abstract_inverted_index.detection | 35 |
| abstract_inverted_index.different | 10 |
| abstract_inverted_index.self-made | 37 |
| abstract_inverted_index.training. | 44 |
| abstract_inverted_index.determined | 89 |
| abstract_inverted_index.end-to-end | 19, 122 |
| abstract_inverted_index.identifies | 63 |
| abstract_inverted_index.processing | 14, 151 |
| abstract_inverted_index.production | 148 |
| abstract_inverted_index.Experiments | 118 |
| abstract_inverted_index.effectively | 132 |
| abstract_inverted_index.efficiency. | 155 |
| abstract_inverted_index.information | 94 |
| abstract_inverted_index.intelligent | 145 |
| abstract_inverted_index.rectangular | 78 |
| abstract_inverted_index.transmitted | 106 |
| abstract_inverted_index.respectively; | 80 |
| abstract_inverted_index.characteristic | 93 |
| cited_by_percentile_year.max | 94 |
| cited_by_percentile_year.min | 89 |
| countries_distinct_count | 1 |
| institutions_distinct_count | 3 |
| citation_normalized_percentile.value | 0.53784583 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |