Tree species recognition with fuzzy texture parameters

Authors:
Ralf Reulke;Norbert Haala
Affiliations:
Institut für Informatik, Computer Vision, Humboldt-Universität zu Berlin, Berlin, Deutschland;Institut für Photogrammetrie (ifp), Universität Stuttgart, Stuttgart, Deutschland
Venue:
IWCIA'04 Proceedings of the 10th international conference on Combinatorial Image Analysis
Year:
2004

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Abstract

The management and planning of forests presumes the availability of up-to-date information on their current state. The relevant parameters like tree species, diameter of the bowl in defined heights, tree heights and positions are usually represented by a forest inventory. In order to allow the collection of these inventory parameters, an approach aiming at the integration of a terrestrial laser scanner and a high resolution panoramic camera has been developed. The integration of these sensors provides geometric information from distance measurement and high resolution texture information from the panoramic images. In order to enable a combined evaluation, in the first processing step a co-registration of both data sets is required. Afterwards geometric quantities like position and diameter of trees can be derived from the LIDAR data, whereas texture parameters are derived from the high resolution panoramic imagery. A fuzzy approach was used to detect trees and differentiate tree species.