According to the center symmetric characteristics of circular image objects, this study proposes an anti-rotation and efficient discriminative binary feature extraction method based on pairs of spatial symmetry structure. This method reconstructs the local coordinate system by radial transform during feature computation, based on it, then local binary pattern with anti-rotation of spatial symmetry regions are extracted. Meanwhile, the annular space is adopted to achieve rotation invariability during the feature pooling operation, which ensures the anti-rotation ability of final feature description. This method are tested in the euro coins, QQ expression, and car logo data set, and the recognition accuracy reached 100%, 100%, and 97.07% respectively, which is superior to traditional LBP and HOG features in euro coins and QQ expression datasets. Moreover, the algorithm is efficient, and the computation time for single point feature extraction is only 0.045 ms.