Abstract
The current work proposes an innovative methodology for the recognition of plant species by using a combination of shape and texture features from leaf images. The leaf shape is modeled using Curvelet Coefficients and Invariant Moments while texture is modeled using a Ridge Filter and some statistical measures derived from the filtered image. As the features are sensitive to geometric orientations of the leaf image, a pre processing step is performed to make features invariant to geometric trans-formations. To classify images to pre-defined classes, a Neuro fuzzy classifier is used. Experimental results show that the method achieves acceptable recognition rates for images varying in texture, shape and orientation.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsReferences
Beghin, T., Cope, J.S., Remagnino, P., Barman, S.: Shape and texture based plant leaf classification. In: International Conference on Advanced Concepts for Intelligent Vision Systems (ACVIS), pp. 345–353 (2010)
Kebapci, H., et al.: Plant image retrieval using color, shape and texture features. Comput. J. 53(1), 1–16 (2010)
Du, J.-X., Zhai, C.-M., Wang, Q.-P.: Recognition of plant leaf image based on fractal dimension feature. Neurocomputing 116, 150–156 (2013)
Yang, L.W., Wang, X.F.: Leaf image recognition using fourier transform based on ordered sequence. Springer LNCS. 7389, 393–400 (2012)
Wang, Q-P., Du, J-X., Zhai, C-M.: Recognition of leaf image based on ring projection wavelet fractal feature. In: International Journal Innovative Computing, Information and Control, pp. 240–246 (2012)
Candès, E., Donoho, D.: Curvelets—a Surprisingly Effective Nonadaptive Representation for Objects with Edges, pp. 1–10. Vanderbilt University Press, Nashville (2000)
Hu, M.K.: Visual pattern recognition by moment invariants. IRE Trans. Inf. Theory 8(2), 179–187 (1962)
Hong, L., Wan, Y., Jain, A.K.: Fingerprint image enhancement: algorithm and performance evaluation. IEEE Trans. PAMI 20(8), 777–789 (1998)
Flavia Dataset: http://sourceforge.net/projects/flavia/files/Leaf%20Image%20Dataset/
Kadir, A., Nogroho, L.E., Susanto, A., Santosa, P.I.: Neural network application on foliage plant identification. Int. J. Comput. Appl. 29, 15–22 (2011)
Wang, X., Liang, J., Guo, F.: Feature extraction algorithm based on dual-scale decomposition and local binary descriptors for plant leaf recognition. Elsevier Digital Image Process. 34, 101–107 (2014)
Caglayan, A., Oguzhan, G., Can, A.B.: A plant recognition approach using shape and color features in leaf images, vol. 8157, pp. 161–170 Springer LNCS (2013)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2016 Springer India
About this paper
Cite this paper
Chaki, J., Parekh, R., Bhattacharya, S. (2016). Plant Leaf Recognition Using Ridge Filter and Curvelet Transform with Neuro-Fuzzy Classifier. In: Nagar, A., Mohapatra, D., Chaki, N. (eds) Proceedings of 3rd International Conference on Advanced Computing, Networking and Informatics. Smart Innovation, Systems and Technologies, vol 43. Springer, New Delhi. https://doi.org/10.1007/978-81-322-2538-6_5
Download citation
DOI: https://doi.org/10.1007/978-81-322-2538-6_5
Published:
Publisher Name: Springer, New Delhi
Print ISBN: 978-81-322-2537-9
Online ISBN: 978-81-322-2538-6
eBook Packages: EngineeringEngineering (R0)