The week's pick
Random Articles
Reseach Article
A Review and a Comparative Study of Various Plant Recognition and Classification Techniques using Leaf Images
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 123 - Number 2 |
| Year of Publication: 2015 |
| Authors: Anand Handa, Rashi Agarwal |
10.5120/ijca2015905247
|
Anand Handa, Rashi Agarwal . A Review and a Comparative Study of Various Plant Recognition and Classification Techniques using Leaf Images. International Journal of Computer Applications. 123, 2 ( August 2015), 20-25. DOI=10.5120/ijca2015905247
Abstract
This paper compares various algorithms that are used for plant classification based on leaf images are presented. The paper reviews the main computational, morphological and image processing methods that have been formulated in recent years. At the end, we conclude with the ongoing work in the present area and the other existing problems in the area. The automatic digital plant classification can be done by extracting various features from its leaves and still there exist possibilities to improve plant species identification through the designing of a new digital automatic plant identification and recognition system. In general different ways can be used with following major steps. Firstly, leaf images are acquired with high quality digital cameras and scanners then the user has to select a base point and reference points are marked on the leaf blades. This step leads to the extraction of several morphological features and these features are used as inputs to a machine learning algorithm. The use of the Probabilistic neural network is done for the above process and for this the network is trained with leaves from different plant species. At last the recognition rate and accuracy are tested for each proposed methodology. All the specified methods work only for plant leaves that are broad and flat or they are more or less two dimensional in nature.
References
- R. C. Gonzalez, R. E. Woods, “Digital Image Processing”. Prentice Hall, 2004.
- 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.
- 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.
- 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.
- X. Gu, J. Du, and X. Wang, “Leaf recognition based on the combination of wavelet transform and gaussian interpolation,” in Proceedings of International Conference on Intelligent Computing 2005, ser. LNCS 3644. Springer, 2005.
- X. Wang, J. Du, and G. Zhang, “Recognition of leaf images based on shape features using a hypersphere classifier,” in Proceedings of International Conference on Intelligent Computing 2005, ser. LNCS 3644. Springer, 2005.
- 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.
- M K HU, “Visual pattern recognition by moment invariants,” IRE Trans. Info Theory, vol IT-8, pp. 179-187, Feb. 1962.
- T.H. Reiss, “The Revised Fundamental Theorem of Moment Invariants”, IEEE Trans. Pattern Anal. Machine Intell., Vol. PAMI-13, No. 8, August 1991, pp 830-834.
- Sidhartha Maître, ”Moment invariant ”,IEEE Preceding vol. 67, no. 4,april 1979.
- Jan Flusser, “Rotation Moment Invariants for Recognition of Symmetric Objects,” IEEE Trans. On image processing, vol. 15, no. 12, pp. 3784-3790, December 2006.
- S. Wu, F. Bao, E. Xu, Y. Wang, Y. Chang, and Q. Xiang, “A Leaf Recognition Algorithm for Plant Classification Using Probabilistic Neural Network,” IEEE 7th International Symposium on Signal Processing and Information Technology, December 2007.
- J.-X. Du, X.-F. Wang and G.-J. Zhang, "Leaf shape based plant species recognition," Applied Mathematics and Computation, vol. 185, 2007.
- 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.
- Sandeep kumar E. “Leaf, colour, Area And Edge Features Based Approach For Identification Of Indian Plants” Indian Journal of Computer Science and Engineering (IJCSE), ISSN : 0976-5166, Vol. 3 No.3 Jun-Jul 2012.
- S. Prasad, P. Kumar and R.C. Tripathi, “Plant leaf species identification using Curvelet transform”, 2nd International Conference on Computer and Communication Technology (ICCCT), Pp. 646–652, 2011.
- 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 2012. Vol. 41 No.1.
- J. Chaki and R. Parekh, “Plant Leaf Recognition using Shape based Features and Neural Network Classifiers”, International Journal of Advanced Computer Science and Applications, Vol 2, No. 10, 2011
- Kue-Bum Lee and Kwang-Seok Hong, “An Implementation of Leaf Recognition System using Leaf Vein and Shape”, International Journal of Bio-Science and Bio-Technology, Vol. 5 No. 2, April 2013.
- Sanjeevan G, “Plant Recognition from Leaf Image through Artificial Neural Network” International Journal of Computer Applications, Jan 2013. Vol. 62 No.17.
- Mei Fern Bong, Ghazali bin Sulong, Mohd Shafry Mohd Rahim, “Recognition of Leaf Based on Its Tip and Base using Centroid Contour Gradient” International Journal of Computer Science Issues, March 2013, Vol. 10, Issue 2, No 2.
- Caner Uluturk and Aybars Ugur, “Recognition of Leaves Based on Morphological Features Derived From Two Half-Regions”
Index Terms
Keywords