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.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Besl, P.J.: Segmentation through variable order surface fitting. IEEE Transactions on Pattern Analysis and Machine Intelligence 10(2), 167–192 (1988)
Friedlaender, K.B.H.: First experience in the application of laserscanner data for the assessment of vertical and horizontal forest structures. In: IAPRS, Part B7, vol. XXXIII, pp. 693–700 (2000)
Haralick, R.M.: Digital step edges from zero-crossings of second directional derivatives. IEEE Transactions on Pattern Analysis and Machine Intelligence PAMI-6(1), 58–68 (1984)
Pal, S.K., Kundu, M.K.: Automatic selection of object enhancement operator with quantitative justification based on fuzzy set theoretic measures. Pattern Recognition Letters 11, 811–829 (1990)
Pietikainen, M.K. (ed.): Texture Analysis in Machine Vision. World Scientific Publishing Company, Singapore (2000)
Korsitzky, H., Reulke, R., Scheele, M., Solbrig, M., Scheibe, K.: EYESCAN - a high resolution digital panoramic camera. In: Klette, R., Peleg, S., Sommer, G. (eds.) RobVis 2001. LNCS, vol. 1998, pp. 77–83. Springer, Heidelberg (2001)
Maas, H.-G., Schneider, D.: Geometric modelling and calibration of a high resolution panoramic camera. Optical 3-D Measurement Techniques VI II, 122–129 (2003)
Aschoff, T., Spiecker, H., Thies, M., Simonse, M.: Automatic determination of forest inventory parameters using terrestrial laserscanning. In: Proceedings of the ScandLaser Scientific Workshop on Airborne Laser Scanning of Forests, pp. 251–257 (2003)
Aschoff, T., Spiecker, H., Thies, M.: Terrestrische laserscanner im forst - für forstliche inventur und wissenschaftliche datenerfassung. AFZ/Der Wald 58 22, 1126–1129 (2003)
Gimel’farb, G., Yu, L.: Image retrieval using colour co-occurrence histograms. In: Image and Vision Computing New Zealand 2003, Palmerston North, New Zealand, pp. 42–47 (2003)
Zadeh, L.A.: Fuzzy sets as a basis for a theory of possibility. Fuzzy Sets and Systems 1, 3–28 (1978)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2004 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Reulke, R., Haala, N. (2004). Tree Species Recognition with Fuzzy Texture Parameters. In: Klette, R., Žunić, J. (eds) Combinatorial Image Analysis. IWCIA 2004. Lecture Notes in Computer Science, vol 3322. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30503-3_45
Download citation
DOI: https://doi.org/10.1007/978-3-540-30503-3_45
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-23942-0
Online ISBN: 978-3-540-30503-3
eBook Packages: Computer ScienceComputer Science (R0)