A target recognition matching method with high reliability

Grayness correlation is a method with high reliability for target recognition. However, there is a lack of reliable guidelines for matching results. Basing on normalized correlation, this thesis uses the SURF (Speed up Robust Features) algorithm of local features of an image to verify matching results. By fully utilizing the global and local information of the image, this method ensures the reliability of the matching results. Emulation tests how that this method is hardly interfered by outside factors and can greatly save time by using parallel calculations. With a high accuracy of matching results, it is applicable for targets recognition.