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Analysis of the Classification Techniques for Plant Identification through Leaf Recognition
Abstract
The field of leaf recognition for plant classification has experienced an increased need for fast and efficient classification algorithms to aid in keeping track of our planet’s endangering inhabitants. This demand has led to the development of several techniques which have revolutionized the area of automatic plant classification. This increase in the number of techniques has given rise to the dilemma of deciding which of these methods possess the best properties and potentials for effective classification. This problem is of particular importance in the botany field where the distortion of information may lead to inaccurate and often neglect identification of important species. Thus, there exists a need to have knowledge about the different classification algorithms in order to see the advantages of each technique. Therefore this paper discusses the various techniques and methods used for plant classification through leaf recognition as reported by various researchers and academicians. In particular, this paper reviews research works based on two categories, namely, contour-based and region-based approaches.
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References
C. Im, H. Nishida, and T. L. Kunii, “Recognizing plant species by leaf shapes – A case study of the Acer family”, Proceedings of Fourteenth International Conference on Pattern Recognition, Vol. 2, pp. 1171-1173, 1998.
C. Lee, and S. Chen, “Classification for Leaf Images”, 16th IPPR Conference on Computer Vision, Graphics and Image Processing (CVGIP 2003)Vol. 8, pp.355-362, 2003.
C. Lee and S. Chen “Classification of leaf images, International Journal of Imaging Systems and Technology”, Vol. 16, Issue 1, pp. 15-23. DOI:10.1002/ima.20063, 2006.
Cotton Incorporated USA “The classification of Cotton”, http://www.cottoninc.com/ ClassificationofCotton, 2009.
D. Zhang, and G. Lu, “A comparative study on shape retrieval using Fourier descriptors with different shape signatures”, International conference on intelligent multimedia and distance education in Fargo, ND, USA, 2001.
F. Mokhtarian, and S. Abbasi, “Matching Shapes With Self-Intersections : Application to Leaf Classification”, IEEE Transactions on Image Processing, Vol. 13, No. 5, pp.653-661, 2004.
G. Zhang, X. Wang, and D. Huang, “A Hypersphere Method For Plant leaves Classification”, Proceedings of 2004 International Symposium on Intelligent Multimedia, Video and Speech Processing, pp. 165-168, 2004.
J. B. Cunha, “Application of image processing techniques in the characterization of plant leafs”, IEEE International Symposium on Industrial Electronics, Vol.1, No.1, pp. 612-616, 2003.
J. Park, E. Hwang, and Y. Nam, “Utilizing venation features for efficient leaf image retrieval”, Journal of Systems and Software, Vol. 81, Issue 1, pp. 71-82, 2008.
L. Mündermann, P. MacMurchy, J. Pivovarov, and P. Prusinkiewicz, “Modeling lobed leaves”, Proceedings of the Computer Graphics International, pp.60-65, 2003.
N. Kumar, S. Pandey, A. Bhattacharya and P. S. Ahuja “Do leaf surface characteristics affect agrobacterium infection in tea [camellia sinensis (l.) o kuntze]?”, J. Biosci., Vol. 29, No. 3, pp. 309–317, 2004.
National Institute for Agricultural Botany, “Chrysanthemum Leaf Classification”, Cambridge, 2005.
P. J. Ykomi, M. R. Jackson, and R. M. Parkin, “Plant Classification Combining Colour and Spectral Cameras for Weed Control Purposes”, IEEE International Symposium on Industrial Electronics, pp. 2039- 2042. DOI: 10.1109/ISIE.2007.4374921, 2007.
P. Tzionas, S. Papadakis and D. Manolakis, “Plant leaves classification based on morphological features and a fuzzy surface selection technique”, Fifth International Conference on Technology and Automation, Thessaloniki, Greece, pp. 365-370, 2005.
Q. Man, C. Zheng, X. Wang and F. Lin, “Recognition of Plant Leaves Using Support Vector Machine”, ICIC 2008, CCIS 15, Springer-Verlag Berlin Heidelberg, pp. 192–199, 2008.
Q. Wu, C. Zhou, and C. Wang, “Feature Extraction and Representation of Plant Leaf for Image Retrieval”, H.T.Shen et al.(eds): APWeb Workshops, Lecture Notes in Computer Science 3842, pp. 127-131, 2006.
S. Abbasi, F. Mokhtarian, and J. Kittler, “Reliable Classification of Chrysanthemum Leaves through Curvature Scale Space”, Proceedings of the First International Conference on Scale-Space Theory in Computer Vision, Utrecht, The Netherlands, pp. 284-295, July 1997.
S. G. Wu, F. S. Bao, E. Y. Xu, Y. Wang, Y. Chang, and Q. Xiang, “A Leaf Recognition Algorithm for Plant Classification Using Probabilistic Neural Network”, IEEE International Symposium on Signal Processing and Information Technology, pp. 11-16, 2007.
T. Saitoh and T. Kaneko, “Automatic Recognition of Wild Flowers”, Proceedings of 15th International Conference on Pattern Recognition, Vol. 2, pp. 507-510, 2000.
T. W. S. Chow, and M. K. M. Rahman, “A new image classification technique using tree-structured regional features”, Neurocomputing, Vol. 70, Issue 4-6, pp. 1040-1050, 2007.
X. Gu, J. Du, and X. Wang, “Leaf Recognition Based on the Combination of Wavelet Transform and Gaussian Interpolation”, Lecture Notes in Computer Science, Springer Berlin / Heidelberg, Vol. 3644/2005, pp. 253-262, 2005.
Y. Nam, and E. Hwang “A Shape-Based Retrieval Scheme for Leaf Images”, Lecture Notes in Computer Science 3767, Y.-S. Ho and H.J. Kim (Eds.), Springer-Verlag, pp. 876-887, 2005.
Y. Nam, E. Hwang, and K. Byeon, “ELIS: An Efficient Leaf Retrieval System”, Lecture Notes in Computer Science 3687, S. Singh et al. (Eds.), Springer-Verlag, pp. 589-597, 2005a.
Y. Nam, E. Hwang, and D. Kim “CLOVER: A mobile Content-Based Leaf Image Retrieval System”, Lecture Notes in Computer Science 3815, E.A. Fox et al.(Eds.), Springer-Verlag, pp. 139-148, 2005b.
Y. Nam, E. Hwang, E. and D. Kim “A similarity-based leaf image retrieval scheme: Joining shape and venation features”, Computer Vision and Image Understanding, Vol. 110, Issue 2, pp. 245-259, 2008.
Z. Wang, D. Feng, and Z. Chi, “Region-based binary tree representation for image classification”, Proceedings of the 2003 International Conference on Neural Networks and Signal Processing, Vol. 1, pp. 232- 235, 2003.
Z. Wang, Z. Chi, and D. Feng, “Shape based leaf image retrieval”, IEEE Proceedings, Visual Image Signal Process, Vol. 150, No. 1, pp. 34-43, 2003.
Z. Wang, Z. Chi, and D. Feng, D. “Fuzzy integral for leaf image retrieval”, Proceedings of the 2002 IEEE International Conference on Fuzzy Systems, Honolulu, USA, Vol.1, pp. 372 – 377, 2002.
Z. Wang, Z. Chi, D., Feng. Q, Wang, “Leaf Image Retrieval with Shape Features”, Lecture Notes in Computer Science: Advances in visual information systems, R.Laurini(Ed.), Springer-Verlag, pp. 477-488, 2000.
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