Accurate forecasting of occurrence time and abundance of insect pests is essential for developing technology of integrated pest management system. Digital image processing algorithms were utilized to automatically recognize rice planthoppers which are major insect pests in the rice cultivation field and were subsequently used to estimate densities in the field for efficient forecasting of insect pests. To the images taken in the rice field, image decomposition, top-hat transformation, threshold, and minimum and maximum filter were implemented for patterning individually the brown planthopper specimens attached at the bottom area of rice stems. In average 95.8cio of images were correctly recognized for estimating densities by the developed system, and the recognition rate was higher than that obtained from direct observations by experienced observers. Furthermore, the size of the recognized specimens was measured and was used for estimating the age structure in the observed brown planthopper populations