Open AccessA Review On Leaves Disease Segmentation And Classification Techniques
Author(s) -
Soumya Ranjan Sahu,
C. S. Panda
Publication year - 2019
Publication title -
international journal of scientific research in science and technology
Language(s) - English
Resource type - Journals
eISSN - 2395-602X
pISSN - 2395-6011
DOI - 10.32628/ijsrst1196333
Subject(s) - segmentation , computer science , livelihood , cluster analysis , plant disease , classifier (uml) , agriculture , artificial intelligence , disease , market segmentation , image segmentation , machine learning , contextual image classification , pattern recognition (psychology) , computer vision , data mining , geography , microbiology and biotechnology , business , image (mathematics) , biology , medicine , marketing , pathology , archaeology
Agriculture plays a major role in our society. Most of the people depend on agriculture for their living. It becomes very important part of society for their livelihood. But there are some problems on agriculture that directly or indirectly affect the human health and also economy. The major problem for agriculture is the plant diseases. This paper is based on a survey of different types of techniques used for segmenting and classification of plant diseases by using image processing techniques. By these techniques, we can easily detect the area of the infected part or can identify the type of disease. This paper gives various techniques used by various authors to detect the disease fast an accurately. They used different types of segmentation techniques like region based, clustering, thresolding etc. to detect the infected part of the leaves and by using the classifier they classify the disease name. The traditional method of naked eye observation can be overcome by introducing these methods. Main focus of our work is to analysis of fast and accurate techniques to identify the plant diseases.