The week's pick
Reseach Article
Leaf Classification based on GLCM Texture and SVM
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 177 - Number 35 |
| Year of Publication: 2020 |
| Authors: Naveen M., Vidyashankara M. S., G. Hemantha Kumar |
10.5120/ijca2020919846
|
Naveen M., Vidyashankara M. S., G. Hemantha Kumar . Leaf Classification based on GLCM Texture and SVM. International Journal of Computer Applications. 177, 35 ( Feb 2020), 18-21. DOI=10.5120/ijca2020919846
Abstract
This paper involves classification of leaves using GLCM (Gray Level Co-occurrence matrix) texture and SVM (Support Vector Machines). GLCM is used for extracting texture feature of leaves. Creating a plant database for quick and efficient classification and recognition is an important step for their conservation. This approach would help to extract useful features of leaf and improve the accuracy of leaf classification. The standard leaf images are subjected to pre-processing. Feature values are extracted from pre-processed image and they are trained and classified. Standard data sets are used for enhancing the properties of the image.
References
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- Abdul Kadir, Lukito Edi Nugroho, and Paulus Insap Santosa, “Leaf classification using shape, color, and texture”, International Journal of Computer Trends & Technology (IJCTT), July-August 2011,pp.225-230.
- C. S. Sumathi and A. V. Senthil Kumar, “Edge and Texture Fusion for Plant Leaf Classification”, International Journal of Computer Science and Telecommunications, Vol 3, Issue 6, June 2012,pp. 6-9.
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- J. S. Cope, P. Remagnino, S. Barman, and P. Wilkin, "Plant texture classification using gabor co-occurrences," In Advances in Visual Computing, Springer Berlin Heidelberg, 2010, pp.669-677.
- Shayan Hati BTech Student, “Plant Recognition from Leaf Image through Artificial Neural Network ” Department of Civil Engineering, Indian Institute of Technology (IIT), Kharagpur International Journal of Computer Applications (0975 – 8887) Volume 62– No.17, January 2013.
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