The week's pick
Random Articles
Reseach Article
Species Classification of Aquatic Plants using GRNN and ANFIS
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 47 - Number 4 |
| Year of Publication: 2012 |
| Authors: S. Abirami, V. Ramalingam, S. Palanivel |
10.5120/7180-9863
|
S. Abirami, V. Ramalingam, S. Palanivel . Species Classification of Aquatic Plants using GRNN and ANFIS. International Journal of Computer Applications. 47, 4 ( June 2012), 47-52. DOI=10.5120/7180-9863
Abstract
This work presents a method for plant species identification using the images of flowers. It focuses on the stable features of flowers such as color, texture and shape. K-means clustering is used to extract the color features. Texture segmentation is done using texture filters. Edge detectors are used to trace the boundary of the image and hence the shape features. Color, texture and shape features are extracted from 400 images of flowers. Classification of plants into dry land plants and aquatic plants, the aquatic plant species into wet and marsh aquatic plants, wet aquatic plants into iridaceae and epilobium family and marsh aquatic plants into malvaceae and onagraceae family, the iridaceae family into babiana and crocus species, the family epilobium into canum and hirsutum, the family malvaceae into mallow and pavonia, the family onagraceae into fuschia and ludwigia species are done using Generalized Regression Neural Network (GRNN) and Adaptive Neural Fuzzy Inference System (ANFIS) classifiers.
References
- Hanife Kebapci, Berrin Yanikoglu and Gozde Unal "Plant Image Retrieval Using Color, Shape and Texture Features" Faculty of Engineering and Natural Sciences, Sabanci University, Istanbul, Turkey. The Computer Journal Advance Access published April 9, 2010.
- Lei Zhang, Jun Kong, Xiaoyun Zeng, Jiayue Ren, "Plant Species Identification Based on Neural Network" Fourth International Conference on Natural Computation. IEEE Computer Society, vol. 5, pp. 90-94, 2008.
- B. Sathya Bama, S. Mohana Valli, S. Raju ,V. Abhai, "Content Based Leaf Image Retrieval (CBLIR) Using Shape, Color and Texture Features". Indian Journal of Computer Science and Engineering (IJCSE), vol. 2, no. 2, pp. 202-211, Apr-May 2011.
- Norma Jean Venable Illustrated by Ann Payne "AQUATIC PLANTS- Guide to Aquatic and Wetland Plants of West Virginia", Cooperative Extension Service West Virginia University Extension and Public Service series 803, May/June, 1914.
- Jiazhi Pan, Hangzhou, Zhejiang panjz "Recognition of plants by leaves digital image and neural network" Yong He Biosystem Engineering and Food Science College, Zhejiang University, pp: 906-910, Dec 2008.
- Ma W. Y. , Yining Deng, and Manjunath B. S. , "Tools for texture/color based search of images" Department of Electrical and Computer Engineering, University of California, Santa Barbara, SPIE Int. Conf. 3106, Human Vision and Electronic Imaging II, pp 496-507, Feb. 1997.
- Hong Fu. , Zheru Chil, Dagan Fengl, and Jiatao Song. J, "Machine Learning Techniques for Ontology-based Leaf Classification" 8th International Conference on Control, Automation, Robotics and Vision Kunming, China, vol: 1, pp: 681-686, 6-9th December 2004.
- David R. Martin, Charless C. Fowlkes, and Jitendra Malik "Learning to Detect Natural Image Boundaries Using Local Brightness, Color, and Texture Cues", IEEE transactions on pattern analysis and machine intelligence, vol. 26, no. 5, pp: 530-549, May 2004.
- Hhuang Lin, He Peng, "Machine Recognition for Broad-Leaved Trees Based on Synthetic Features of Leaves Using Probabilistic Neural Network" International Conference on Computer Science and Software Engineering, pp: 871-877, 2008.
- Krishna Singh, Indra Gupta, Sangeeta Gupta, "SVM-BDT PNN and Fourier Moment Technique for of Leaf Shape" International Journal of Signal Processing, Image Processing and Pattern Recognition, vol. 3, no. 4, December, pp. 67-78, 2010.
- Corinna Cortes, Vladimar Vapnik, Editor: Lorenza Saitta, "Support-Vector Networks" Machine Learning, Kluwer Academic Publishers, Boston. Manufactured in The Netherlands. AT&T Bell Labs, Holmdel, vol. 20, pp. 273-297, USA, 1995.
- Rahmadhani M. and Yeni Herdiyeni "Shape and Vein Extraction on Plant Leaf Images Using Fourier and B-Spline Modeling", AFITA International Conference, the Quality Information for Competitive Agricultural Based Production System and Commerce, pp. 306-310, 2010.
- Jyh-Shing, Roger Jang, ANFIS: "Adaptive-Network-Based Fuzzy Inference System" IEEE transactions on systems, man and Cybernetics, vol. 23, no. 3, pp. 665-685, May/June 1993.
- Chuan-Min Zhai and Ji-Xiang Du, "Applying Extreme Learning Machine to Plant Species Identification", Proceedings of the IEEE International Conference on Information and Automation, Zhangjiajie, China, pp: 879-884. June 20 -23, 2008.
- Matlab Image Processing Toolbox™ 7 User's Guide, Version 7. 2 (Release 2011a).
- Rafael C. Gonzalez, Richard E. Woods, "Digital Image Processing using Matlab". PHI learning Private Limited, New Delhi, 2008.
- Chih-Wei Hsu, Chih-Chung Chang, and Chih-Jen Lin, "A Practical Guide to Support Vector Classification" Department of Computer Science, National Taiwan University, Taipei, April 2010.
Index Terms
Keywords