For vehicle detection in infrared image,a vehicle detection algorithm based on histogram of oriented gradient (HOG)feature and supervised locality preserving projection (SLPP)was proposed.Firstly,in order to enhance the performance of detection,the grey information was obtained by using the image segmentation,and then the HOG feature was obtained by enhancing the contour information without increasing the dimensionality of the feature.Secondly,the dimension of traditional HOG feature is too high which affect the efficiency and accuracy of vehicle detection.Therefore,the SLPP is used to reduce the dimension of features.Finally,to realize the vehicle detection,the extreme learning machine (ELM)is adopted to train the low dimensional feature of sample image.The presented approach is tested in the reality infrared images.The experimental results show that the proposed method for vehicle detection in infrared images has better performance.Comparing with the result of HOG feature,the feature dimension of SLPP -SHOG decreases from 1764 to 30;the detection precision increases by 16.03%;the F1-measure rises by 8.79%;and the detection time reduces by 3.1 ms.