Automated Rice Leaf Disease Detection Using Color Image Analysis
By R.A.D.L. Pugoy and V.Y. Mariano, in 3rd International Conference on Digital Image Processing (ICDIP 2011), Chengdu, China, 15-17 April 2011
Abstract
In rice-related institutions such as the International Rice Research Institute, assessing the health condition of a rice plant through its leaves, which is usually done as manual eyeball exercise, is important to come up with good nutrient and disease management strategies.
In this paper, an automated system that can detect diseases present in a rice leaf using color image analysis is presented. In the system, the outlier region is first obtained from a rice leaf image to be tested using histogram intersection between the test and healthy rice leaf images. Upon obtaining the outlier, it is then subjected to a threshold-based K-means clustering algorithm to group related regions into clusters. Then these clusters are subjected to further analysis to finally determine the suspected diseases of the rice leaf.
Mariano Details
Vladimir Y. Mariano,
Source:: http://www.ics.uplb.edu.ph/node/477
By R.A.D.L. Pugoy and V.Y. Mariano, in 3rd International Conference on Digital Image Processing (ICDIP 2011), Chengdu, China, 15-17 April 2011
Abstract
In rice-related institutions such as the International Rice Research Institute, assessing the health condition of a rice plant through its leaves, which is usually done as manual eyeball exercise, is important to come up with good nutrient and disease management strategies.
In this paper, an automated system that can detect diseases present in a rice leaf using color image analysis is presented. In the system, the outlier region is first obtained from a rice leaf image to be tested using histogram intersection between the test and healthy rice leaf images. Upon obtaining the outlier, it is then subjected to a threshold-based K-means clustering algorithm to group related regions into clusters. Then these clusters are subjected to further analysis to finally determine the suspected diseases of the rice leaf.
Mariano Details
Vladimir Y. Mariano,
Associate Professor, Institute of Computer Science,
The University of the Philippines Los Baños.
