A MOBILE APPLICATION FOR ROBUST FEATURE EXTRACTION AND CULTIVAR CLASSIFICATION OF LEAVES

Authors

  • DOMINIK L. MICHELS Multimedia, Simulation and Virtual Reality Group University of Bonn, Germany
  • GERRIT A. SOBOTTKA Multimedia, Simulation and Virtual Reality Group University of Bonn, Germany

Keywords:

Mobile Application, Leaf Classification, Feature-Based Classification, eature Extraction, Gabor Filter, Edge Tracing, Support Vector Machines

Abstract

We illustrate the development of an application for cultivar classification of leaf images based on the extraction of the network of its main veins that runs on mobile devices like smart phones or tablets. Such mobile devices can be docked to farming robots in order to support the farming process. Our application uses an efficient Gabor filter-based tracing algorithm which is able to perform a robust network extraction. The results are used as input data for the classification with a support vector machine. In order to demonstrate the advantageous behavior and the robustness of this method, we perform an evaluation on a test set consisting of 150 light transmitted images of different vine leaves.

 

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References

J. S. Cope, P. Remagnino, S. Barman, and P. Wilkin. The extraction of venation from leaf images

by evolved vein classifiers and ant colony algorithms. In ACIVS (1), pages 135–144, 2010.

I. P. G. R. Institute. Descriptors for Grapevine: (Vitis Spp.). Descriptors IBPGRI. International

Plant Genetic Resources Institute, 1997.

S. Kirkpatrick, C. D. Gelatt, and M. P. Vecchi. Optimization by simulated annealing. Science,

:671–680, 1983.

C.-L. Lee and S.-Y. Chen. Classification of leaf images. International Journal of Imaging Systems

and Technology, 16(1):15–23, 2006.

Y. Li, Z. Chi, and D. D. Feng. Leaf vein extraction using independent component analysis. In

Systems, Man and Cybernetics, 2006. SMC ’06. IEEE International Conference on, volume 5,

pages 3890–3894, 2006.

K. Pearson. On lines and planes of closest fit to systems of points in space. Philosophical Magazine,

:559–572, 1901.

WEKA 3. Data Mining with Open Source Machine Learning Software in Java.

S. Wu, F. Bao, E. Xu, Y.-X. Wang, Y.-F. Chang, and Q.-L. Xiang. A leaf recognition algorithm

for plant classification using probabilistic neural network. In Signal Processing and Information

Technology, 2007 IEEE International Symposium on, pages 11 –16, dec. 2007.

X. Zheng and X. Wang. Leaf vein extraction based on gray-scale morphology. International

Journal of Image, Graphics and Signal Processing, 2:25–31, 2010.

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Published

2013-09-15

How to Cite

MICHELS, D. L. ., & SOBOTTKA, G. A. . (2013). A MOBILE APPLICATION FOR ROBUST FEATURE EXTRACTION AND CULTIVAR CLASSIFICATION OF LEAVES. Journal of Mobile Multimedia, 9(1-2), 145–154. Retrieved from https://journals.riverpublishers.com/index.php/JMM/article/view/4651

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