The invention relates to a method for searching images for vehicles on the basis of a convolutional neural network. The method comprises the steps that images sets of different vehicles are collected, training is conducted in a typical convolutional neural network model by taking the same vehicles as positive sample pairs and taking the different vehicles as negative sample pairs, similarity differences or classification errors are minimized, a group of vehicle feature expression methods are learned, a result of a data layer can be taken as texture features of the vehicles after the vehicle images are propagated forwards in the convolutional neural network model, the similarity between the features of the vehicles to be retrieved and the features of retrieve set vehicles is calculated through the features, and a result for searching the images for the vehicles is obtained by conducting sorting according to the similarity. According to the method, the vehicle image appearance expression methods are learned through the convolutional neural network, and compared with SIFT features, HoG features and the like, the purposiveness is higher, the features are more visual, the extra metric learning process is not needed, the searching accuracy and precision are significantly improved, the feature dimension number can be controlled to be at the small magnitude, and quick searching in a large image library can be achieved.