A Lightweight RPR-DETR for Prohibited Item Detection in X-Ray Security Inspection Images

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Object overlap in X-ray security inspection images can introduce interference into feature representation and increase the difficulty of prohibited item detection. To address this problem, an improved RT-DETR model named RPR-DETR is developed in this study. First, the original backbone is replaced with a lightweight RGCSPELAN structure, where structural reparameterization is incorporated into hierarchical feature aggregation to decrease model complexity. Second, a Pola-CGLU encoder is introduced to model relationships across different spatial regions while retaining local neighborhood interaction. In addition, an RFPN structure is employed to reorganize feature transformation and scale conversion among different feature levels. On the OPIXray dataset, RPR-DETR obtains an mAP50 of 90.0%, exceeding RT-DETR-R18 by 1.2 percentage points. Compared with RT-DETR-R18, RPR-DETR uses 31.2% fewer parameters and requires 22.6% fewer FLOPs. On DvXray, the proposed model improves mAP50 by 1.4 percentage points over the baseline. The experimental results indicate that RPR-DETR provides a better balance between prohibited item detection performance and model complexity.