Grape Leaf Disease Detection, Classification and Analysis by using Spatial Graylevel Dependence Matrices
Keywords:
cluster shade (CS), cluster prominence (CP)Abstract
Plant diseases need to be controlled for at least two reasons: to maintain the quality of food produced by
farmers around the world and in order to reduce the food-borne illnesses originated from infected plants. Thus,
automatic identification of “unhealthy” regions in leaf images is a useful tool for various biological research projects
aiming the control of diseases or characterization of plant defense mechanisms. There is a wide variety of plant diseases
caused by either environmental factors (nutrition, moisture, temperature, etc.) or by other organisms (fungi, bacteria,
viruses). However, in most cases the common symptom is the change of the leaf color. We propose and experimentally
evaluate a software solution for automatic detection and classification of Grape plant leaf diseases.
