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Rice Leaf Diseases Data Set
Download: Data Folder, Data Set Description

Abstract: There are three classes/diseases: Bacterial leaf blight, Brown spot, and Leaf smut, each having 40 images. The format of all images is jpg.

Data Set Characteristics:  

Multivariate

Number of Instances:

120

Area:

Computer

Attribute Characteristics:

Integer

Number of Attributes:

N/A

Date Donated

2019-04-14

Associated Tasks:

Classification

Missing Values?

N/A

Number of Web Hits:

21727


Source:

Jitesh P. Shah, Email: jitesh2k12 '@' gmail.com, Institute: Department of Information Technology, Dharmsinh Desai University,Nadiad-387001, Gujarat, INDIA. Creator Name: Harshadkumar B. Prajapati, Email: prajapatihb.it '@' ddu.ac.in, Institute: Department of Information Technology, Dharmsinh Desai University,Nadiad-387001, Gujarat, INDIA. Creator Name: Vipul K. Dabhi, Email: vipuldabhi.it '@' ddu.ac.in, Institute: Department of Information Technology, Dharmsinh Desai University,Nadiad-387001, Gujarat, INDIA.


Data Set Information:

The dataset was created by manually separating infected leaves into different disease classes. We had consulted the farmers and had asked them to provide names of diseases for sample leaves. Farmers had provided names in their native languages (Gujarati) and we identified and verified English names of those diseases by consulting with experts of agriculture field.

This dataset was used for Detection and Classification of Rice Plant Diseases. As part of the work, the following activities were carried out (1) How to extract various image features (2) which image processing operations can provide needed information (3) which image features can provide substantial input for classification. The survey work is available in IEEE conference paper:


A Survey on Detection and Classification of Rice Plant Diseases, available at [Web Link]. A classification model was developed using SVM. The detailed information is available in the published journal article:Detection and classification of rice plant diseases, in Intelligent Decision Technologies, IOS Press, available at [Web Link]


Attribute Information:

Image Format: .jpg, The images were captured with a white background, in direct sunlight. The images were reduced to the desired resolution for processing.


Relevant Papers:

(1) Prajapati HB, Shah JP, Dabhi VK. Detection and classification of rice plant diseases. Intelligent Decision Technologies. 2017 Jan 1;11(3):357-73, doi: 10.3233/IDT-170301. (2) Shah JP, Prajapati HB, Dabhi VK. A survey on detection and classification of rice plant diseases. InCurrent Trends in Advanced Computing (ICCTAC), IEEE International Conference on 2016 Mar 10 (pp. 1-8). IEEE.



Citation Request:

Prajapati HB, Shah JP, Dabhi VK. Detection and classification of rice plant diseases. Intelligent Decision Technologies. 2017 Jan 1;11(3):357-73, doi: 10.3233/IDT-170301.


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