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This paper researched image matching issue and proposed a feature point matching algorithm to improve the BRIEF algorithm. The proposed algorithm generated the feature point description operator according to the difference signs and the difference magnitudes relation between the random point and the feature point. BRIEF was sensitive to noise because the small difference magnitude was more susceptible to the noise. To solve this problem, this paper determined a small pixel difference threshold by the neighborhood mean value of the BRIEF. Comparing the Hamming distance between descriptions realized the feature points matching. Compared with BRIEF and ORB algorithm, the experiments prove that the operator has higher discriminant, simple calculation and good noise suppression performance. And the matching accuracy is higher. [ABSTRACT FROM AUTHOR]