一种机场智能安全监控与预警方法
By inspecting airport pavement, and using RGB channel normalization and patented technology for detection, the method introduces red-green and yellow-blue contrast channels for detection, combined with multi-scale detection, and employs contrast detection technology, the problem of low detection accuracy in existing technologies has been solved, achieving accurate detection and risk warning for small foreign objects.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- CHENGDU SHUANGLIU INT AIRPORT
- Filing Date
- 2026-05-08
- Publication Date
- 2026-07-17
AI Technical Summary
Existing technologies for airport pavement inspection are easily affected by the inherent texture of the pavement and changes in lighting, resulting in low detection accuracy and difficulty in effectively identifying small foreign objects.
RGB channel normalization and range dynamic compression are used to extract the red-green and yellow-blue contrast channel images. Two-dimensional discrete Fourier transform is performed to generate multi-scale contrast color saliency maps. The relative deviation coefficient is calculated and the saliency maps are fused. The detection is then performed using a dual-channel mask-guided neural network.
It significantly improves the detection accuracy of small foreign objects, effectively suppresses pavement background interference, and enhances the accuracy and robustness of detection.
Smart Images
Figure CN122157171B_ABST