3和0.554%。 When the four conventional edge detection methods such as the Sobel are applied to detect the multiple-structure edges of the Long Wing Laodelphax Striatellus (Fallen) image including the wing and the claw, it will be influenced by the pixels noise and the edge will not be clear. Also the morphology of erode single element edge detection method are adopted and the result is not ideal, as the breakpoints is 10 and the minimum loss rate of the pixels is 0.689%. In order to improve the ability for detecting the edge, the image was divided into several areas due to the multi-edges so that the edge detection in every area was simplified. Subsequently, the erode with dilate edge detecting operators was constructed, which could be used to detect the different edges in every areas. The results indicate that the multi-areas combined with morphology multi-structures method for detecting the Long Wing Laodelphax Striatellus (Fallen) edge is better, and the breakpoints is 3 and the minimum loss rate of the pixels is 0.554%.