The ground standby aircraft images taken by the aircraft are often affected by the distortion of rotation,scaling,affine etc,and the noise effects can make partial of target contour missing.To solve this problem,a new feature,entitled contour invariant feature,was proposed and applied in recognition of standby aircraft.Based on the object gray image obtained through segmentation,the ellipse fitting method was utilized to normalize the direction of the targets,and the global contour features were extracted.Then,the contour was divided into four parts according to the key points coordinates,and the local features were extracted. The global and local features were served as an input vector of the trained neural networks to distinguish whether the source image was the destination image.Two groups of target recognition comparative experiments were made.The results show that this method can obtain high recognition rate in spite of the noise pollution or incomplete contour extraction,which has better performance than state-of-the-art algorithms such as moments feature.