Image Processing Techniques in Plant Disease Diagnosis: Application Trend in Agriculture

Abstract

AbstractIn agriculture, plant diseases cause significant economic losses every year and are major threats against food security. To control the infestation at the earliest stage and minimize crop loss, precise diagnosis of plant diseases is the only way. The diagnostic process usually relies on the in-field visual identification by agricultural experts with rich experience. However, for a large number of underdeveloped and developing countries, human experts are scarce and expensive. As an alternative, image processing techniques are becoming popular for automated plant disease diagnosis in agriculture. Several image processing systems have been proposed worldwide during the last one and a half decades. Aside from a mere literature survey, this paper presents a statistical study of the application trend of various image processing techniques used to design image processing systems for plant disease diagnosis in agriculture. This study will be very beneficial for aspirant researchers in the future to design such systems.KeywordsImage processingPlant disease diagnosisApplication trendSegmentation techniquesFeature extraction techniquesMachine learning techniques