The invention belongs to the field of recognizing types of vehicles through
computer image processing, and relates to a method and
system for detecting and recognizing a feature and a brand of a vehicle in a
static image by means of a digital picture
processing technique. A method for detecting the vehicle in the
static image is combined with a vehicle logo detecting method which is based on an
AdaBoost framework in the method. The method and
system for detecting and recognizing the feature of the vehicle in the static images comprises a training part and a detecting part. The training part includes the following steps of manufacturing a vehicle logo sample, collecting an image containing the vehicle logo from
the Internet, positioning the vehicle logo, and extracting the vehicle logo
image based on position information; calculating a sample feature, constructing 5 different rectangular features with each rectangular feature corresponding to one Haar feature; training a
cascade classifier, inputting the training sample acquired from the last step and conducting training, and finally connecting strong classifiers and multiple corresponding weak classifiers obtained in training in series. The detecting part includes the following steps: loading the image to be detected, converting the image into a grey-scale image and conducting
histogram equalization, loading the vehicle logo classifiers which include threshold values of the strong classifiers and the weak classifiers and rectangular feature information corresponding to the selected features, conducting
cascade vehicle logo detection with the detected image firstly passing the detection of the former strong classifiers. If the detected image is not the vehicle logo image, the detected image can be excluded at the front end, and only the vehicle logo can finally pass the detection of the strong classifiers at various different levels.