Leaf Region Segmentation for Plant Leaf Disease Detection using Color Conversion and Flood Filling

Abstract

Leaves are the primary sources for identifying a healthy plant and identifying many plant diseases. When leaf disease has not been correctly analyzed and early detection is not taken may produce a severe effect on the plants, which results in the loss of yield and quality of the production. Identifying or monitoring the diseases manually requires a tremendous amount of work and a lot of processing time. To overcome this, today, image processing has been widely used to identify conditions in plants to increase production. This paper has proposed a methodology to segment the leaf region using different color space models and flood filling algorithms. This system can be future used to classify the type of leaf disease.