Geometrid larvae detection using contour feature

Early detection and prediction of pests in field automatically is an important topic in modern agriculture engineering. In this paper, we design a program that can detect geometrid larvae automatically using image processing technology. Firstly, according to color characterization of larvae, we extract brown larvae candidates from image with background of green leaves. We use morphological operation to correct the candidate's regions. Then we use elliptic Fourier transform to represent the contours of larval candidates. The representation is a vector. Thereafter we compare all the possible contour vectors of the larvae with the selected larval contour vector. According to the distance between vectors, we determine whether the contour is a true larval contour. The experimental results show that our method can effectively extract geometrid larvae in tea garden images.