一种基于自适应CSF算法的农作物株高提取方法及系统
By using the adaptive CSF algorithm, which combines crop characteristics and growth stages to dynamically adjust parameters, the adaptability and efficiency problems of the traditional CSF algorithm in crop height measurement are solved, and high-precision, fully automated plant height extraction is achieved.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- SOUTHWEAT UNIV OF SCI & TECH
- Filing Date
- 2026-05-21
- Publication Date
- 2026-07-17
AI Technical Summary
Traditional CSF algorithms rely on human experience for parameter setting in crop height measurement, resulting in poor adaptability, low processing efficiency, and inadequate boundary handling, making it difficult to meet the needs of large-scale real-time monitoring.
The adaptive CSF algorithm is adopted. By dynamically adjusting parameters and combining point cloud density, crop type, growth stage and planting pattern, a multi-dimensional parameter mapping strategy is used. Combined with block parallel processing and voting fusion mechanism, it realizes automated ground point separation and canopy height model generation.
The algorithm's adaptability and processing efficiency have been improved, reducing false positives in corn furrows and failures in wheat lodging detection, ensuring boundary quality, and achieving fully automated, high-precision plant height measurement.
Smart Images
Figure CN122244135B_ABST