This paper is published in Volume-5, Issue-3, 2019
Area
Computer Science Engineering
Author
Sakshi
Co-authors
Vachana Shree, Vinutha H., Srinath G. M., Sowmyashree H. V.
Org/Univ
S. J. C. Institute of Technology, Chikkaballapur, Karnataka, India
Pub. Date
13 May, 2019
Paper ID
V5I3-1362
Publisher
Keywords
Image processing, Classification technique, Color histogram component Introduction

Citationsacebook

IEEE
Sakshi, Vachana Shree, Vinutha H., Srinath G. M., Sowmyashree H. V.. The survey on detection of plant diseases by image processing technique, International Journal of Advance Research, Ideas and Innovations in Technology, www.IJARIIT.com.

APA
Sakshi, Vachana Shree, Vinutha H., Srinath G. M., Sowmyashree H. V. (2019). The survey on detection of plant diseases by image processing technique. International Journal of Advance Research, Ideas and Innovations in Technology, 5(3) www.IJARIIT.com.

MLA
Sakshi, Vachana Shree, Vinutha H., Srinath G. M., Sowmyashree H. V.. "The survey on detection of plant diseases by image processing technique." International Journal of Advance Research, Ideas and Innovations in Technology 5.3 (2019). www.IJARIIT.com.

Abstract

The traditional agricultural system is causing various problems regarding the production of crops and it is the main reason for plant diseases. There are few diseases like rice blast, brown spot, red stripe and downy fungal which cause significant reduction in both quality and quantity of agricultural products. As we people were busier in our daily life, we need a technology which can automatically detect symptoms of plants and give information about it for farmers, so they can easily diagnosis it. So the technological world and agro scientists have found a solution for the major problem facing by our farmers regarding plant diseases. There are many plant diseases which can cause various problems in the human race. We can implement a system which detects and prevents plant diseases easily by using “IMAGE PROCESSING TECHNIQUE”. This technique initially finds the infected region, later finds features like color, texture, and shape. This can be achieved by 3 steps, first color transformation structure for the input RGB image is created, thus the green pixels are masked and removed by segmentation, later texture statics are computed, and finally extracted features are passed through the classifiers. The major techniques involved in the process are, color space, color histogram, grey level co-occurrence matrix, etc…and classification techniques like support vector machine (SVM), back propagation (BP).
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