ijett-book-cover  International Journal of Engineering Trends and Technology (IJETT)          
© 2013 by IJETT Journal
Volume-4 Issue-2                       
Year of Publication : 2013
Authors :  Anant Bhardwaj , Manpreet Kaur


Anant Bhardwaj , Manpreet Kaur. "A REVIEW ON PLANT RECOGNITION AND CLASSIFICATION TECHNIQUES USING LEAF IMAGES". International Journal of Engineering Trends and Technology (IJETT). V4(2):86-91 Feb 2013. ISSN:2231-5381. www.ijettjournal.org. published by seventh sense research group


Automatic digital plant classification and retrieval can be achieved by extracting features from its leaves. There are various opportunities to improve plant species identification due to computerization through the designing of a convenient automatic plant recognition system. Many different approaches consist of some major parts. First, images of leaf are acquired with di gital camera or scanners. Then the user can selects the base point of the leaf and a few reference points on the leaf blades or done this automatically. Then several morphological features are extracted. These features are used as inputs to the classifier system for discrimination as probabilistic neural network. The network was trained with leaves from different plant species. Then the recognition accuracy of the propo sed method has been tested. The method works only for the plants with broad flat leaves w hich are more or less two dimensional in nature. This paper presented various effective algorithms used for plant classification using leaf images and review the main computational, morphological and image processing methods that have been used in recent y ears and we conclude with a discussion of ongoing work and outstanding problems in the area.


[1] R. C. Gonzalez, R. E. Woods, “Digital Image Processing”. Prentice Hall, 2004.
[2] Z. Wang, Z. Chi, and D. Feng, “Shape based leaf image retrieval,” IEEE Proceedings Vision, Image and Signal Processing, vol. 150, no. 1, February 2003.
[3] H. Fu, Z. Chi, D. Feng, and J. Song, “Machine learning techniques for ontology - based leaf classification,” IEEE 2004 8th International Conference on Control, Automation, Robotics and Vision, Kunming, China, 2004.
[4] J. Du, D. Huang, X. Wang, and X. Gu, “Computer - aided plant species identification (CAPSI) based on leaf shape matching technique,” Transactions of the Institute of Measurement and Control. 28, 3 (2006) pp. 275 - 284.
[5] X. Gu, J. Du, and X. Wang, “Leaf recognition based on the combinat ion of wavelet transform and gaussian interpolation,” in Proceedings of International Conference on Intelligent Computing 2005, ser. LNCS 3644. Springer, 2005.
[6] X. Wang, J. Du, and G. Zhang, “Recognition of leaf images based on shape features using a hypers phere classifier,” in Proceedings of International Conference on Intelligent Computing 2005, ser. LNCS 3644. Springer, 2005.
[7] J. Du, D. Huang, X. Wang, and X. Gu, “Shape recognition based on radial basis probabilistic neural network and application to plant species identification,” in Proceedings of 2005 International Symposium of Neural Networks, ser. LNCS 3497. Springer, 2005.
[8] M K HU, “Visual pattern recognition by moment invariants,” IRE Trans. Info Theory, vol IT - 8, pp. 179 - 187, Feb. 1962.
[9] T.H. Reiss, “T he Revised Fundamental Theorem of Moment Invariants”, IEEE Trans. Pattern Anal. Machine Intell., Vol. PAMI - 13, No. 8, August 1991, pp 830 - 834.
[10] Sidhartha Maître, ”Moment invariant ”,IEEE Preceding vol. 67, no. 4,april 1979.
[11] Jan Flusser, “Rotation Moment I nvariants for Recognition of Symmetric Objects,” IEEE Trans. On image processing, vol. 15, no. 12, pp. 3784 - 3790, December 2006.
[12] S. Wu, F. Bao, E. Xu, Y. Wang, Y. Chang, and Q. Xiang, “A Leaf Recognition Algorithm for Plant Classification Using Probabilist ic Neural Network,” IEEE 7th International Symposium on Signal Processing and Information Technology, December 2007.
[13] J. - X. Du, X. - F. Wang and G. - J. Zhang, "Leaf shape based plant species recognition," Applied Mathematics and Computation, vol. 185, 2007.
[14] J. Hossain and M.A. Amin, “Leaf shape identification based plant biometrics”, 13th International Conference on Computer and Information Technology (ICCIT), Pp. 458 - 463, 2010.
[15] Sandeep kumar E. “Leaf, colour, Area And Edge Features Based Approach For Identifi cation Of Indian Plants” Indian Journal of Computer Science and Engineering (IJCSE), ISSN : 0976 - 5166, Vol. 3 No.3 Jun - Jul 2012.
[16] S. Prasad, P. Kumar and R.C. Tripathi, “Plant leaf species identification using Curvelet transform”, 2nd International Conferen ce on Computer and Communication Technology (ICCCT), Pp. 646 – 652, 2011.
[17] Abdul Kadir , L . E . Nugroho , A . susanto , P . Insap Santosa , “Experiments of Zernike Moments for Leaf Identification” , Journal of Theoretical and Applied Information Technology , 15 July 201 2. Vol. 41 No.1 .
[18] V. Cheung and K. Cannons, “An Introduction to Probabilistic Neural Networks”, http://www.psi.toronto.edu/~vincent/research/presentations /PNN.pdf, (2003).
[19] J. Slens, “A Tutorial on Principal Component Analysis”, http://www.snl.salk.edu/~sh lens/pca.pdf, (2009).

Plant Leaf Classification, PNN, PCA, Texture Analysis and Radial Basis Function, Moments Invariants, Neural Networks.