Recognition of Leaf Ailments and Categorization using Image Processing

Abstract

Recognizing the plant illnesses is significant in directive to avert the
wounded in the field and quantity of the agricultural product. The
education of the plant diseases is the education of visually noticeable
designs seen on the plant. Health monitoring and disease discovery on
plant is very dangerous for agriculture field. It is problematic to monitor
the plant diseases physically. There is obligation of huge quantity of work,
expertise in the plant diseases, and also need the extreme processing
time. Without accurate disease, good control actions cannot be used
at the appropriate time. The impartial of this system is to contrivance
image analysis and classification methods for detection of leaf diseases
and classification. The planned system contains of four parts. They are
(1) Image pre-processing (2) Segmentation of the leaf using K-means
clustering to determine the diseased areas (3) feature extraction and (4)
Classification of diseases. Texture structures are extracted using statistical
Gray-Level Co-occurrence Matrix (GLCM) features and classification is
done using Support Vector Machine (SVM).

How to cite this article:
Kadam P, Jadhav AR, Jadhav AK et al. Recognition
of Leaf Ailments and Categorization using Image
Processing. J Adv Res Image Proc Appl 2018;
2(2): 7-10.