Z. Wang, Z. Chi, D. Feng, and Q. Wang, “Leaf image retrieval with shape features”, in Advances in Visual Information Systems, ser. Lecture Notes in Computer Science, R. Laurini, Ed. Springer Berlin / Heidelberg, 2000, vol. 1929, pp. 41–52.
Z. Wang, Z. Chi, D. Feng, “Shape based leaf image retrieval”, Vision, Image and, Signal Processing, 150(1), pp. 34–43, feb 2003.
Y. Shen, C. Zhou, K. Lin, “Leaf image retrieval using a shape based method”, in Artificial Intelligence Applications and Innovations, ser. IFIP International Federation for Information Processing, D. Li and B. Wang, Eds. Springer, Boston, 2005, vol. 187, pp. 711–719.
C.-L. Lee and S.-Y. Chen, “Classification of leaf images”, International Journal of Imaging Systems and Technology, vol. 16, no. 1, pp. 15–23, 2006.
C. Caballero and M. C. Aranda, “Plant species identification using leaf image retrieval”, in Proc. of the ACM International Conference on Image and Video Retrieval. New York, NY, USA: ACM, 2010.
N. Sakai, S. Yonekawa, A. Matsuzaki, and H. Morishima, “Two-dimensional image analysis of the shape of rice and its application to separating varieties”, Journal of Food Engineering, vol. 27, no. 4, pp. 397–407, 1996.
A. R. Backes and O. M. Bruno, “Plant leaf identification using multi-scale fractal dimension”, in Proc. of the 15th International Conference on Image Analysis and Processing. Berlin, Heidelberg: Springer-Verlag, 2009, pp. 143–150.
B. S. Bama, S. M. Valli, S. Raju, and V. A. Kumar, “Content based leaf image retrieval (cblir) using shape, color and texture features”, Indian Journal of Computer Science and Engineering, vol. 2, no. 2, pp. 202–211, 2011.
N. Otsu, “A threshold selection method from gray-level histograms”, IEEE Transactions on Systems, Man and Cybernetics, vol. 9, no. 1, pp. 62–66, jan. 1979.
T. Jolliffe, Principal Component Analysis, ser. Springer Series in Statistics. Springer New York, 2006.
C. Cortes and V. Vapnik, “Support-vector networks”, in, Machine Learning, 1995, pp. 273–297.
M. A. Turk and A. P. Pentland, “Face recognition using eigenfaces”, in Proc. of IEEE Computer Society Conference on Computer Vision and, Pattern Recognition, jun 1991, pp. 586–591.