Robot vision environmental perception method based on hybrid features
机器人的混合特征视觉环境感知方法

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.