Abstract
For the machine vision object matching,the feature list correlation algorithm can be adopted in the calculation of the matching similarity measurement.As a result,the processing time is able to be decreased considerably,and the objects can also be clearly recognized due to the high values of the coefficients and the high values of the Peak Signal-to-Noise Ratio(PSNR).A feature list object matching method based on the oriented Smallest Univalue Segment Assimilating Nucleus(SUSAN)features was proposed.The feature pixels with oriented SUSAN features were added to the feature lists and the similarity was based on the normalized absolute error of feature pixel points.The supposed algorithm is verified by the experiments.
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