Method, system, device and medium for automatically identifying vehicle-mounted scrap steel in full load state
By employing deep network image segmentation, single connected component search, and minimum rectangle contour optimization methods, the problem of occlusion recognition of scrap steel on vehicles under full load conditions was solved, achieving high-precision recognition of the main body of the scrap steel.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- ANQING NORMAL UNIV
- Filing Date
- 2024-06-21
- Publication Date
- 2026-07-24
AI Technical Summary
When fully loaded, the characteristics of scrap steel on board are obscured, making it difficult for existing technologies to efficiently identify scrap steel targets inside the truck, resulting in inaccurate assessment accuracy.
A deep network image segmentation method is used in conjunction with breadth-first search of single connected components, minimum rectangle contour method, and minimum cost translation optimization method to gradually extract and correct the main image of scrap steel, thereby improving the recognition accuracy.
By combining deep networks and a two-stage optimization strategy, the problem of fuzzy feature recognition of scrap steel targets under full load conditions is effectively solved, and the recognition accuracy of scrap steel main body is significantly improved.
Smart Images

Figure CN118898834B_ABST