BSMD-YOLOv8: Enhancing YOLOv8 for Book Signature Marks Detection Article Swipe
Long Guo
,
Lubin Wang
,
Qiang Yu
,
Xiaolan Xie
·
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.3390/app142310829
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.3390/app142310829
In the field of bookbinding, accurately and efficiently detecting signature sequences during the binding process is crucial for enhancing quality, improving production efficiency, and advancing industrial automation. Despite significant advancements in object detection technology, verifying the correctness of signature sequences remains challenging due to the small size, dense distribution, and abundance of low-quality signature marks. To tackle these challenges, we introduce the Book Signature Marks Detection (BSMD-YOLOv8) model, specifically designed for scenarios involving small, closely spaced objects such as signature marks. Our proposed backbone, the Lightweight Multi-scale Residual Network (LMRNet), achieves a lightweight network while enhancing the accuracy of small object detection. To address the issue of insufficient fusion of local and global feature information in PANet, we design the Low-stage gather-and-distribute (Low-GD) module and the High-stage gather-and-distribute (High-GD) module to enhance the model’s multi-scale feature fusion capabilities, thereby refining the integration of local and global features of signature marks. Furthermore, we introduce Wise-IoU (WIoU) as a replacement for CIoU, prioritizing anchor boxes with moderate quality and mitigating harmful gradients from low-quality examples. Experimental results demonstrate that, compared to YOLOv8n, BSMD-YOLOv8 reduces the number of parameters by 65%, increases the frame rate by 7 FPS, and enhances accuracy, recall, and mAP50 by 2.2%, 8.6%, and 3.9% respectively, achieving rapid and accurate detection of signature marks.
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Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.3390/app142310829
- https://www.mdpi.com/2076-3417/14/23/10829/pdf?version=1732284368
- OA Status
- gold
- Cited By
- 1
- References
- 23
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4404635555
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4404635555Canonical identifier for this work in OpenAlex
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https://doi.org/10.3390/app142310829Digital Object Identifier
- Title
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BSMD-YOLOv8: Enhancing YOLOv8 for Book Signature Marks DetectionWork title
- Type
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2024Year of publication
- Publication date
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2024-11-22Full publication date if available
- Authors
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Long Guo, Lubin Wang, Qiang Yu, Xiaolan XieList of authors in order
- Landing page
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https://doi.org/10.3390/app142310829Publisher landing page
- PDF URL
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https://www.mdpi.com/2076-3417/14/23/10829/pdf?version=1732284368Direct link to full text PDF
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goldOpen access status per OpenAlex
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https://www.mdpi.com/2076-3417/14/23/10829/pdf?version=1732284368Direct OA link when available
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Computer science, Signature (topology), Correctness, Data mining, Frame (networking), Feature (linguistics), Pattern recognition (psychology), Process (computing), Artificial intelligence, Algorithm, Computer network, Mathematics, Linguistics, Geometry, Philosophy, Operating systemTop concepts (fields/topics) attached by OpenAlex
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1Total citation count in OpenAlex
- Citations by year (recent)
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2025: 1Per-year citation counts (last 5 years)
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- Related works (count)
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10Other works algorithmically related by OpenAlex
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| primary_location.raw_source_name | Applied Sciences |
| primary_location.landing_page_url | https://doi.org/10.3390/app142310829 |
| publication_date | 2024-11-22 |
| publication_year | 2024 |
| referenced_works | https://openalex.org/W7000415296, https://openalex.org/W3195969653, https://openalex.org/W4389920160, https://openalex.org/W4303578732, https://openalex.org/W4321459483, https://openalex.org/W4382059335, https://openalex.org/W2193145675, https://openalex.org/W4388823657, https://openalex.org/W2565639579, https://openalex.org/W2963857746, https://openalex.org/W4385823324, https://openalex.org/W3034971973, https://openalex.org/W4402979889, https://openalex.org/W3034552520, https://openalex.org/W4239999461, https://openalex.org/W3194790201, https://openalex.org/W4386076325, https://openalex.org/W4398756379, https://openalex.org/W6793164127, https://openalex.org/W3035414587, https://openalex.org/W4386076083, https://openalex.org/W3106250896, https://openalex.org/W2746542255 |
| referenced_works_count | 23 |
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| corresponding_author_ids | https://openalex.org/A5102834936, https://openalex.org/A5100717180 |
| countries_distinct_count | 1 |
| institutions_distinct_count | 4 |
| corresponding_institution_ids | https://openalex.org/I19820366, https://openalex.org/I38706770, https://openalex.org/I4210115570 |
| citation_normalized_percentile.value | 0.63345213 |
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| citation_normalized_percentile.is_in_top_10_percent | False |