@article{(Open Science Index):https://publications.waset.org/pdf/10001823,
	  title     = {Fuzzy Inference System Based Unhealthy Region Classification in Plant Leaf Image},
	  author    = {K. Muthukannan and  P. Latha},
	  country	= {},
	  institution	= {},
	  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).},
	    journal   = {International Journal of Computer and Information Engineering},
	  volume    = {8},
	  number    = {11},
	  year      = {2014},
	  pages     = {2103 - 2107},
	  ee        = {https://publications.waset.org/pdf/10001823},
	  url   	= {https://publications.waset.org/vol/95},
	  bibsource = {https://publications.waset.org/},
	  issn  	= {eISSN: 1307-6892},
	  publisher = {World Academy of Science, Engineering and Technology},
	  index 	= {Open Science Index 95, 2014},
	}