This paper presents an antibody network approach for vehicle detection from high resolution satellite imagery.This approach regards the vehicle detection procedure as a procedure that antibodies recognize danger antigens

where vehicles are "dangerous antigens" and vehicle detection templates are "antibodies".In this paper

some vehicle images are collected as learning examples

and an antiboby network is proposed to learn optimal "antibodies"

which can be used to detect vehicles through the proposed matching algorithm.Experiments on Quickbird satellite images are given to show the feasibility and performance of the proposed approach.