Opto-Electronic Engineering, Volume. 52, Issue 4, 240286(2025)
Adaptive panoramic focusing X-ray image contraband detection algorithm
Figures & Tables(15)
Fig. 4. Structure of multi-path two-dimensional information integration (MPTI)
Fig. 5. Structure of dual cross attention mechanism (DCA). (a) DCA module; (b) CCA module; (c) SCA module
Fig. 6. Structure of frequency adaptive dilated convolution (FADC)
Fig. 7. Structure of panoramic dynamic focus detection head (PDF_Detect)
Fig. 8. Comparison of evaluation indicators between the YOLOv8n and improved model
Fig. 9. F1-curve comparison diagram between the baseline model YOLOv8n (left) and improved model (right) on the SIXray dataset
Fig. 10. Convergence curves of the improved algorithm on the SIXray dataset
Table 1. Ablation experiment results of the improved algorithm in the SIXray dataset
View tableView in ArticleTable 1. Ablation experiment results of the improved algorithm in the SIXray dataset
No. YOLOv8n A B C P/% R/% mAP@0.5/% mAP@0.5∶0.95/% Params/M GFLOPs 1 √ × × × 91.3 84.2 89.7 66.1 3.01 8.1 2 √ √ × × 93.8 85.4 91.8 68.6 4.17 11.3 3 √ × √ × 92.0 84.0 90.6 66.2 2.48 6.2 4 √ × × √ 91.8 84.9 91.3 66.5 2.78 7.7 5 √ √ √ × 94.1 86.3 92.2 69.4 2.86 7.8 6 √ √ × √ 94.7 86.7 92.6 70.7 3.59 9.4 7 √ × √ √ 94.3 87.3 91.9 68.6 2.65 6.8 8 √ √ √ √ 94.6 88.8 93.3 72.4 2.92 7.9
Table 2. Comparison results of the accuracy of ablation experiments by category
View tableView in ArticleTable 2. Comparison results of the accuracy of ablation experiments by category
No. YOLOv8n A B C AP/% mAP@0.5/% GU KN WR PL SC 1 √ × × × 97.8 86.5 87.6 94.5 84.8 89.7 2 √ √ × × 98.5 87.8 90.5 95.3 87.4 91.8 3 √ × √ × 98.2 86.9 88.6 95.1 85.2 90.6 4 √ × × √ 98.4 87.4 88.4 94.6 87.9 91.3 5 √ √ √ × 99.2 88.4 90.7 96.0 86.5 92.2 6 √ √ × √ 99.1 88.2 92.1 95.8 86.8 92.6 7 √ × √ √ 98.7 86.8 92.6 95.6 85.8 91.9 8 √ √ √ √ 99.4 89.0 93.5 96.4 87.1 93.3
Table 3. Comparison experiment results on the SIXray dataset
View tableView in ArticleTable 3. Comparison experiment results on the SIXray dataset
Model AP/% P/% R/% mAP@0.5/% FPS Params/M GFLOPs GU KN WR PL SC SSD 91.6 74.8 69.8 80.9 83.4 83.5 70.8 79.6 60.4 26.28 62.7 Faster R-CNN 89.2 79.4 80.1 86.4 84.2 87.9 75.1 85.5 31 136.72 369.8 YOLOv5n 98.7 88.2 82.6 90.5 79.7 92.7 78.7 87.9 101 2.50 7.1 YOLOv6 97.1 83.7 87.0 92.2 81.1 87.4 82.1 88.2 121.6 4.23 11.8 YOLOv7-Tiny 97.7 82.6 85.0 89.8 78.7 86.6 81.3 86.7 94.5 6.02 13.2 YOLOv8n 97.8 86.5 87.6 94.5 84.8 91.3 84.2 89.7 108.6 3.01 8.1 YOLOv9 98.4 86.6 88.0 92.9 84.8 91.4 82.5 90.1 111.5 2.27 8.2 YOLOv10n 98.3 87.5 90.2 95.8 86.0 90.1 85.7 91.4 116.3 2.71 8.4 Ours 99.4 89.0 93.5 96.4 87.1 94.6 88.8 93.3 125.9 2.92 7.9
Table 4. Comparison experiment results on OPIXray dataset
View tableView in ArticleTable 4. Comparison experiment results on OPIXray dataset
Model AP/% P/% R/% mAP@0.5/% FPS Params/M GFLOPs ST FO SC UT MU SSD 33.5 73.4 89.5 64.1 80.8 70.5 62.8 65.7 53.2 26.28 62.7 Faster R-CNN 68.3 88.7 90.0 82.5 89.4 89.0 82.7 84.8 25.4 136.72 369.8 YOLOv5n 72.6 92.4 98.5 85.1 93.3 87.8 83.9 88.4 109.8 2.50 7.1 YOLOv6 78.6 92.0 98.3 87.1 94.6 89.2 86.1 90.1 119.5 4.23 11.8 YOLOv7-Tiny 65.7 91.6 97.9 84.0 84.0 90.7 81.4 86.4 102.9 6.02 13.2 YOLOv8n 76.9 94.3 98.0 85.3 93.8 90.5 85.5 89.7 116.8 3.01 8.1 YOLOv9 75.0 91.6 98.6 83.0 93.5 88.5 85.2 88.3 111.7 2.27 8.2 YOLOv10n 68.9 93.8 97.4 81.8 93.4 88.3 81.5 84.9 108.5 2.71 8.4 Ours 79.4 95.9 99.2 88.5 96.1 93.2 89.4 92.5 123.8 2.92 7.9
Tools
Get Citation
Copy Citation Text
Liqun Cui, Yingying Yang, Haibo Jin, Zhengwei Wu. Adaptive panoramic focusing X-ray image contraband detection algorithm[J]. Opto-Electronic Engineering, 2025, 52(4): 240286
Paper Information
Category: Article
Received: Dec. 5, 2024
Accepted: Feb. 17, 2025
Published Online: Jun. 11, 2025
The Author Email: Yingying Yang (杨莹莹)
© Copyright 2018-2021 | Chinese Laser Press.
All Rights Reserved 沪ICP备15018463号-20