SURF( Speed-Up Robust Features ) is a robust and fast descriptor for many applications , but neither can it detect sym-metrical matches , nor can it consider global context .This paper combines symmetrical SURF with global context .It enables SURF to detect symmetrical matches through mirroring transformation and reduces mismatches when local descriptors are similar . The proposed algorithm is used in vehilce detection .The experiments show that symmetrical SURF with global context improves the accuracy of feature matches and vehicle detection .%SURF（ Speed-Up Robust Features ）是一种鲁棒且快速的算法，可以应用于多种场合，但是它不能检测对称匹配，也没有考虑全局信息。本文将对称SURF和全局信息结合起来，既通过镜像变换增强了SURF检测对称匹配特征的能力，又可以在图像有多个相似区域的情况下减少错误匹配。该算法应用在车辆检测中，实验表明结合全局信息的对称SURF提高了特征匹配的准确率，从而提高了车辆检测的准确率。
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