WASET
	@article{(Open Science Index):https://publications.waset.org/pdf/10358,
	  title     = {Real-Time Specific Weed Recognition System Using Histogram Analysis},
	  author    = {Irshad Ahmad and  Abdul Muhamin Naeem and  Muhammad Islam},
	  country	= {},
	  institution	= {},
	  abstract     = {Information on weed distribution within the field is
necessary to implement spatially variable herbicide application.
Since hand labor is costly, an automated weed control system could be
feasible. This paper deals with the development of an algorithm for
real time specific weed recognition system based on Histogram
Analysis of an image that is used for the weed classification. This
algorithm is specifically developed to classify images into broad and
narrow class for real-time selective herbicide application. The
developed system has been tested on weeds in the lab, which have
shown that the system to be very effectiveness in weed identification.
Further the results show a very reliable performance on images of
weeds taken under varying field conditions. The analysis of the results
shows over 95 percent classification accuracy over 140 sample images
(broad and narrow) with 70 samples from each category of weeds.},
	    journal   = {International Journal of Agricultural and Biosystems Engineering},
	  volume    = {2},
	  number    = {4},
	  year      = {2008},
	  pages     = {104 - 107},
	  ee        = {https://publications.waset.org/pdf/10358},
	  url   	= {https://publications.waset.org/vol/16},
	  bibsource = {https://publications.waset.org/},
	  issn  	= {eISSN: 1307-6892},
	  publisher = {World Academy of Science, Engineering and Technology},
	  index 	= {Open Science Index 16, 2008},
	}