1. A vehicle detection method for detecting a vehicle image in measured images based on hybrid image template HIT, comprising the following steps: Step S 1 : collecting one or more vehicle images as training images; Step S 2 : utilizing an information projection algorithm to learn all of image patches for representing vehicle object in the HIT from the training images and to compute image likelihood probability distribution of this hybrid image template, wherein the HIT consists of the multiple patches with different image features which are categorized as sketch patch, texture patch, color patch and flatness patch, wherein the image likelihood probability distribution indicates occurrence probability of the HIT in conditions of the training image data; Step S 3 : detecting regions in which an image block of the HIT is present in the input testing image to acquire candidate vehicle regions in which the vehicles are located in the testing images; Step 3 - 1 - 6 : using the patches in the HIT and the image likelihood probability to compute vehicle detection scores of the vehicle candidates region; Step S 3 - 1 - 7 : selecting the vehicle candidate regions with the maximum vehicle detection scores, comparing the maximum vehicle score with the predefined vehicle detection threshold; if the maximum vehicle detection score is no less that the vehicle detection threshold, determining the corresponding vehicle candidate region as a vehicle object, and determining the location and detail sketch information of the vehicle object; Step S 32 : removing the determined vehicle object from the testing image and using the remaining image to detect a next vehicle object and location and detail sketch information thereof by performing above steps, repeating above steps to detect all vehicle objects and location and detail sketch information thereof with an iterative method; and visually indicating in the input testing image the candidate regions determined to be vehicle objects.