An image processing and analysis algorithm was developed to identify the fall armyworm damage on corn plants. The developed program segmented the larvae damage on the image in two stages: a coarse and fine classification. The coarse stage applied a threshold technique on image blocks of 60 x 60 pixels. The fine stage was based on a neural network classifier which classifies image blocks of 3 x 3 pixels. The algorithm accuracy was accessed by evaluating the error matrix based on 80 and 75 image blocks of the coarse and fine stages, respectively. The algorithm presented an overall accuracy of 80.74%.
machine vision; precision farming; artificial neural networks
