Similarity Based Cross-Section Segmentation in Rough Log End Images

Author:

Schraml Rudolf,Uhl Andreas

Publisher

Springer International Publishing

Reference32 articles.

1. Wu, J., Liew, D.: A computer vision method for detection of external log cracks and pith in log cross-section images. In: Procs. of the World Automation Congress: International Symposium on Intelligent Automation and Control (ISIAC 2000), Hawaii, USA (2000)

2. Hanning, T., Kickingereder, R., Casasent, D.: Determining the average annual ring width on the front side of lumber. In: Osten, W., Kujawinska, M., Creath, K. (eds.) Proceedings of SPIE: Optical Measurement Systems for Industrial Inspection, Munich, Germany, vol. 5144, pp. 707–716 (2003)

3. Österberg, P., Ihalainen, H., Ritala, R.: Method for analyzing and classifying wood quality through local 2d spectrum of digital log end images. In: Proceedings of International Conference on Advanced Optical Diagnostics in Fluids, Tokyo, JP (2004)

4. Norell, K., Borgefors, G.: Estimation of pith position in untreated log ends in sawmill environments. Computers and Electronics in Agriculture 63, 155–167 (2008)

5. Schraml, R., Uhl, A.: Pith estimation on rough log end images using local fourier spectrum analysis. In: Proceedings of the 14th Conference on Computer Graphics and Imaging (CGIM 2013), Innsbruck, AUT (2013)

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