A database for automatic classification of forest species

Author:

Martins J.,Oliveira L. S.,Nisgoski S.,Sabourin R.

Publisher

Springer Science and Business Media LLC

Subject

Computer Science Applications,Computer Vision and Pattern Recognition,Hardware and Architecture,Software

Reference17 articles.

1. Thomas L., Milli L.: A robust gm-estimator for the automated detection of external defects on barked hardwood logs and stems. IEEE Trans. Signal Proc. 55, 3568–3576 (2007)

2. Huber H.A.: A computerized economic comparison of a conventional furniture rough mill with a new system of processing. For. Prod. J. 21(2), 34–39 (1971)

3. Buechler, D.N., Misra, D.K.: Subsurface detection of small voids in low-loss solids. In: First ISA/IEEE Conference Sensor for Industry, pp. 281–284 (2001)

4. Tou, J.Y., Lau, P.Y., Tay Y.H.: Computer vision-based wood recognition system. In : Proceedings of International Workshop on Advanced Image Technology (2007)

5. Tou, J.Y., Tay, Y.H., Lau, P.Y.: One-dimensional grey-level co-occurrence matrices for texture classification. In: International Symposium on Information Technology (ITSim 2008), pp. 1–6 (2008)

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