Research on defect detection algorithm of complex texture ceramic tiles based on visual attention mechanism
Aiming at the difficulty of detecting the surface defects of complex texture tiles, a salient target detection method based on the human visual attention mechanism is proposed and used for the detection of tile surface defects. Firstly, the image of ceramic tile surface is pretreated using the singl...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | zho |
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EDP Sciences
2022-04-01
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| Series: | Xibei Gongye Daxue Xuebao |
| Subjects: | |
| Online Access: | https://www.jnwpu.org/articles/jnwpu/full_html/2022/02/jnwpu2022402p414/jnwpu2022402p414.html |
| _version_ | 1797422315484479488 |
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| author | OUYANG Zhou ZHANG Huailiang TANG Ziyang PENG Ling YU Sheng |
| author_facet | OUYANG Zhou ZHANG Huailiang TANG Ziyang PENG Ling YU Sheng |
| author_sort | OUYANG Zhou |
| collection | DOAJ |
| description | Aiming at the difficulty of detecting the surface defects of complex texture tiles, a salient target detection method based on the human visual attention mechanism is proposed and used for the detection of tile surface defects. Firstly, the image of ceramic tile surface is pretreated using the single-scale SSR light correction method and bilateral filtering method; Secondly, according to the principle of contrast and high-frequency suppression in the visual attention mechanism, aiming at the "imaging" and "aggregation" characteristics of complex background textures, a detection model based on the visual attention mechanism is established to determine and mark defects.According to the contrast principle and high-frequency suppression principle in visual attention mechanism, feature extraction of ceramic tile surface is carried out. Then, the image color patch weight salient map and image feature fused salient map are obtained, and the two maps are fused according to the image saliency criteria.Finally, the marked ceramic tile defects are determined and marked.Finally the marked ceramic tile defects are obtained. This defect detection algorithm and the other two algorithms are applied to three kinds of randomly selected complex texture ceramic tiles. The experimental results show that compared with other algorithms, our algorithm can achieve a comprehensive detection rate of more than 96% for complex texture ceramic tiles, and can obtain a good effect of ceramic tile defect detection as well. |
| first_indexed | 2024-03-09T07:30:26Z |
| format | Article |
| id | doaj.art-932fe6b4597a45e49021bf0616f5024e |
| institution | Directory Open Access Journal |
| issn | 1000-2758 2609-7125 |
| language | zho |
| last_indexed | 2024-03-09T07:30:26Z |
| publishDate | 2022-04-01 |
| publisher | EDP Sciences |
| record_format | Article |
| series | Xibei Gongye Daxue Xuebao |
| spelling | doaj.art-932fe6b4597a45e49021bf0616f5024e2023-12-03T06:25:20ZzhoEDP SciencesXibei Gongye Daxue Xuebao1000-27582609-71252022-04-0140241442110.1051/jnwpu/20224020414jnwpu2022402p414Research on defect detection algorithm of complex texture ceramic tiles based on visual attention mechanismOUYANG Zhou0ZHANG Huailiang1TANG Ziyang2PENG Ling3YU Sheng4State Key Laboratory of High Performance and Complex Manufacturing, Central South UniversityState Key Laboratory of High Performance and Complex Manufacturing, Central South UniversityState Key Laboratory of High Performance and Complex Manufacturing, Central South UniversityState Key Laboratory of High Performance and Complex Manufacturing, Central South UniversityState Key Laboratory of High Performance and Complex Manufacturing, Central South UniversityAiming at the difficulty of detecting the surface defects of complex texture tiles, a salient target detection method based on the human visual attention mechanism is proposed and used for the detection of tile surface defects. Firstly, the image of ceramic tile surface is pretreated using the single-scale SSR light correction method and bilateral filtering method; Secondly, according to the principle of contrast and high-frequency suppression in the visual attention mechanism, aiming at the "imaging" and "aggregation" characteristics of complex background textures, a detection model based on the visual attention mechanism is established to determine and mark defects.According to the contrast principle and high-frequency suppression principle in visual attention mechanism, feature extraction of ceramic tile surface is carried out. Then, the image color patch weight salient map and image feature fused salient map are obtained, and the two maps are fused according to the image saliency criteria.Finally, the marked ceramic tile defects are determined and marked.Finally the marked ceramic tile defects are obtained. This defect detection algorithm and the other two algorithms are applied to three kinds of randomly selected complex texture ceramic tiles. The experimental results show that compared with other algorithms, our algorithm can achieve a comprehensive detection rate of more than 96% for complex texture ceramic tiles, and can obtain a good effect of ceramic tile defect detection as well.https://www.jnwpu.org/articles/jnwpu/full_html/2022/02/jnwpu2022402p414/jnwpu2022402p414.htmldefect detectionsalient object detectionillumination correctioncomplex texturevisual attention mechanism |
| spellingShingle | OUYANG Zhou ZHANG Huailiang TANG Ziyang PENG Ling YU Sheng Research on defect detection algorithm of complex texture ceramic tiles based on visual attention mechanism Xibei Gongye Daxue Xuebao defect detection salient object detection illumination correction complex texture visual attention mechanism |
| title | Research on defect detection algorithm of complex texture ceramic tiles based on visual attention mechanism |
| title_full | Research on defect detection algorithm of complex texture ceramic tiles based on visual attention mechanism |
| title_fullStr | Research on defect detection algorithm of complex texture ceramic tiles based on visual attention mechanism |
| title_full_unstemmed | Research on defect detection algorithm of complex texture ceramic tiles based on visual attention mechanism |
| title_short | Research on defect detection algorithm of complex texture ceramic tiles based on visual attention mechanism |
| title_sort | research on defect detection algorithm of complex texture ceramic tiles based on visual attention mechanism |
| topic | defect detection salient object detection illumination correction complex texture visual attention mechanism |
| url | https://www.jnwpu.org/articles/jnwpu/full_html/2022/02/jnwpu2022402p414/jnwpu2022402p414.html |
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