Fuzzy Inference System Based Unhealthy Region Classification in Plant Leaf Image

Authors: K. Muthukannan, P. Latha

Abstract:

In addition to environmental parameters like rain, temperature diseases on crop is a major factor which affects production quality & quantity of crop yield. Hence disease management is a key issue in agriculture. For the management of disease, it needs to be detected at early stage. So, treat it properly & control spread of the disease. Now a day, it is possible to use the images of diseased leaf to detect the type of disease by using image processing techniques. This can be achieved by extracting features from the images which can be further used with classification algorithms or content based image retrieval systems. In this paper, color image is used to extract the features such as mean and standard deviation after the process of region cropping. The selected features are taken from the cropped image with different image size samples. Then, the extracted features are taken in to the account for classification using Fuzzy Inference System (FIS).

Keywords: Image Cropping, Classification, Color, Fuzzy Rule, Feature Extraction.

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1107427

References:

[1] A. Moghad Damzadeh and N. Bourbakis, “A Fuzzy Region Growing Approach for Segmentation of Color Images”, Pattern Recognition, 1997, pp.867- 881.
[2] L. A. Zadeh; “Fuzzy Sets”, Information and Control, 1965, Vol. 8, pp. 338-353
[3] F. Meyer,” Color image segmentation,” In IEEE International Conference on Image Processing and its Applications, May 1995. Maastricht, The Netherlands, pp.303–306.
[4] Rafael Gonzalez, Richard E. Woods, Digital Image Processing, Third edition, Pearson Education, Prentice-Hall, Inc., 2008, pp 642-643.
[5] K. Muthukannan and Dr. P. latha, “clustering techniques based crops image segmentation“, International Journal of computer and Applications, 2012, pp.33-37.
[6] S. Sulzberger, N. Tschicholde S. Vestli, “FUN: Optimization of Fuzzy Rule Based Systems Using Neural Networks”, Proceedings of IEEE Conference on Neural Networks, San Francisco, March 1993, pp. 312- 316.
[7] L. Aurdal, “Image Segmentation beyond thresholding”, Norsk Regnescentral, 2006.
[8] Al-Bashish, D., M. Braik and S. Bani-Ahmad, 2011. Detection and classification of leaf diseases using K-means-based segmentation and neural networks based classification. Inform. Technol. J, DOI:10.3923/itj.2011, January, 2011, pp. 267-275.
[9] Al Bashish, D. Braik, M.; Bani-Ahmad, S. “A frame work for detection and classification of plant leaf and stem diseases, IEEE Conference Publication, DOI: 10.1109/ICSIP.2010.
[10] Libo Liu, Guomin Zhou, “Extraction of the Rice Leaf Disease Image Based on BP Neural Network”, IEEE, 2009.
[11] Vishakha Metre, Jayshree Ghorpade, “An Overview of the Research on Texture Based Plant Leaf Classification”, IJCSN International Journal of Computer Science and Network, Vol 2, Issue 3, 2013ISSN (Online): pp.2277-5420.
[12] Zacharias N. Voulgaris, “Discernibility Conceptin Classification Problems”, University of London, May 2009.