Mean Shift Segmentation Applied to ADS40 Data for Automatic Forest Detection
National Forest Inventories (NFI) are essential for countrywide estimations of a wide range of forest functions. Our research aim is to derive measurable forest features out of airborne image data by using automatic computer-vision based methods. This paper focuses on tree layer detection of high resolution ADS40 data for automation. Preliminary experimental results of mean-shift segmentation method combined with curvature features from airborne laser scanning (ALS) for automatic tree layer detection are presented. Further research is needed to connect separate tree patches into forests according to specific forest definitions.
Zuyuan Wang Ruedi Boesch Lars Waser Christian Ginzler
Dept. of Land Resource Assessment, Swiss Federal Research Institute WSL
国际会议
2009 IEEE International Conference on Information and Automation(2009年 IEEE信息与自动化国际学术会议)
珠海、澳门
英文
1099-1103
2009-06-22（万方平台首次上网日期，不代表论文的发表时间）