An image-matching method for robot environmental perception based on hybrid features from color histograms based on the scale-invariant feature transform (SIFT) is proposed.The SIFT is combined with color histograms to make a compromise between high perception accuracy and real-time processing needs. First

images are processed by making an average of the lightness

then the extracted features are added to the main color histogram

which is more robust against lightness and dynamics in the environment.The number of SIFT values is controlled and local color statistical information is added to the SIFT

which is more accurate and faster for real-time matching.After wards

the process of features-retrieval is accelerated by hierarchical matching.Finally

the scheme is optimized using the proposed reasoning method based on previous knowledge from databases

to further improve the accuracy of perception the simulation and experiment results show that when the scale of the database is growing

the advantage of the proposea method proposed is prominent.