Orchard pests monitoring is very important in precise pest management. The pests trapped by high-voltage current in orchard show different postures, which increase the difficulty of image automatic identification. A posture description-based method has been proposed to automatically represent image boundary and identify certain common pests in orchards. The performance of proposed method in posture description with rotation, translation and wing scale of image edge was tested. Posture feature vector and similarity difference threshold were determined by the calculation of average normalized Fourier descriptors(FDs) and discrete degree. Three types of pests with 200 sample images were tested, and it found that correct rate of target pest Dichocrocis punctiferalis (Guenee) was 86.7% and error rate was 2.6% when discrete degree threshold was 0.02126. The experiment results indicate that this approach has a stable description ability for posture-shape and good recognition performance.