An algorithm of extraction of vehicles based on random projection depth function is proposed for accurately extracting vehicles with different colors in outdoor parking lots.The random projection depth function can effectively distinguish the center and outlier of the data set in RGB color space

and in this way

the vehicles whose color characteristics act as outlier are highlighted.First

the random projection depth function is used to sort the color characteristic of each pixel to obtain random projection depth value

forming the depth field image; Then

morphological closed operation is carried out for the depth field image

and an appropriate random projection depth value is selected as the threshold to binarize the image; Finally

the vehicles are accurately extracted from the parking lot by decision tree algorithm and morphological operations.The experimental results show that the random projection depth function can effectively deal with the same body with different spectrum phenomenon of various color vehicles in remote sensing images.The vehicles of different colors are highlighted in the depth field image

which can effectively improve the efficiency of vehicle extraction

and extraction of vehicles from parking lot of remote sensing images can be realized accurately by combining random projection depth function and simple post-processing.