An Efficient Color Based Segmentation And Feature Extraction Framework For Leaf Disease Detection In Smart Agriculture

Document Type : Primary Research paper


1 Department of EEE,AMET Deemed to be University, Chennai,Tamil Nadu, India

2 Department of ECE, Indian Institute of Information Technology, Trichy


Internet of Things and Artificial Intelligence has led to the advancements in smart
agriculture to improve our country’s economy. This paper focusses on developing an
efficient framework for automatic detection of diseases in plant leaves during the onset of
diseases. Timely detection and accurate identification of diseases is helpful in preventing
the spread of the diseases thereby reducing the crop damage significantly. A novel color
component based segmentation process is proposed in this work. To evaluate the
performance of the developed algorithm Python IDE was used and metrics such as
detection accuracy and classification accuracy were used.