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Reseach Article

Article:Automated Binary based Tree Species Identification

by Ugege Peter E., Ugbogu Omokafe A.
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 11 - Number 6
Year of Publication: 2010
Authors: Ugege Peter E., Ugbogu Omokafe A.
10.5120/1585-2125

Ugege Peter E., Ugbogu Omokafe A. . Article:Automated Binary based Tree Species Identification. International Journal of Computer Applications. 11, 6 ( December 2010), 30-33. DOI=10.5120/1585-2125

@article{ 10.5120/1585-2125,
author = { Ugege Peter E., Ugbogu Omokafe A. },
title = { Article:Automated Binary based Tree Species Identification },
journal = { International Journal of Computer Applications },
issue_date = { December 2010 },
volume = { 11 },
number = { 6 },
month = { December },
year = { 2010 },
issn = { 0975-8887 },
pages = { 30-33 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume11/number6/1585-2125/ },
doi = { 10.5120/1585-2125 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T19:59:52.557530+05:30
%A Ugege Peter E.
%A Ugbogu Omokafe A.
%T Article:Automated Binary based Tree Species Identification
%J International Journal of Computer Applications
%@ 0975-8887
%V 11
%N 6
%P 30-33
%D 2010
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Although automated species identification for many reasons is not yet widely employed, efforts towards the development of automated species identification systems within the last decade is extremely encouraging; that such an approach has the potential to make valuable contribution towards reducing the burden of routine identification. In this work, we developed a system that uses binary numbers generated from the morphological characters of trees to uniquely identify all Nigerian tree species.

References
  1. Gaston K. J. and O’Neill M. A. 2004 Automated species identification: why not?, Phil. Trans. Roy. Soc. London, vol. B359 (March 2004) pp. 655–667
  2. France I., Duller A. W. G., Duller G. A. T. , and Lamb H. F. 2000 A new approach to automated pollen analysis Quatern. Sci. Rev. vol. 19, 537–546
  3. Gauld I. D., O’Neill M. A. and Gaston K. J. 2000 Driving Miss Daisy: the performance of an automated insect identification system,” in Hymenoptera:evolution, biodiversity and biological control, A. D. Austin and M. Dowton, Eds. Collingwood, VIC: CSIRO, pp. 303–312.
  4. Chesmore D. 2000 Methodologies for automating the identification of species, Proc. Inaugral Meeting of the BioNET-International. Group for Computer-Aided Taxonomy (BIGGAT), D. Chesmore, L. Yorke, P. Bridge and S. Gallagher, Egham: BioNET-International Technical Secretariat, (2000), pp. 3–12 .
  5. Banarse D.S., France I. and Duller A. W. G. 2000 Analysis and application of a self-organising image recognition neural network, Adv. Engng Software, vol. 31, pp 937–944.
  6. Wu J. and Zhou Z. H. 2002 Face recognition with one training per person. Pattern Recognistion Lett., vol. 23, pp 1711 –1719,
  7. Gou B., Lam K. M., Lin K. H., and Siu W. C., 2003 Human face recognition based on spartially weighted Hausdorff distance, Pattern Recognistion Lett., vol. 24, pp 499 –507
  8. He Y., Tian J., Luo X., and Zhang T., 2003 Image enhancement and minutiae matching in fingerprint verification. Pattern Recognistion Lett., vol. 24, pp 1349 –1360
  9. Lu G., Zhang D. and Wang K., 2003 Palm print recognition using eigenpalms features. Pattern Recognistion Lett., vol. 24, pp 1463–1467.
  10. Tsalakanidou F., Tzovaras D., and Strintzis M. G. 2003 Use of depth and colour eigenfaces for face recognition. Pattern Recognistion Lett., vol. 24, pp 1427–1435
  11. Keay R. W. J., Onochie C. F. A., and Stanfield D. P.1964 Nigerian Trees Vol. II. Nigerian National Press Ltd., Apapa.
  12. Ugege P. E. Ugbogu O. A. Jayeola, O. A. Halidu S. K, and Oyeleke O. O. 2007 Computer Aided Tree Species identification System. Journal of Forestry Research and Management, vol 4., pp 18-24
Index Terms

Computer Science
Information Sciences

Keywords

Automated tree species identification morphological binary