A Vocabulary Forest-based object matching processor is proposed to speed up the feature matching stage for the object recognition system with high accuracy. Adopting Reusable-Vocabulary Tree architecture and hardware sharing technique reduces area, as well as adopting propagate-and-compute-array architecture in the combiner and external database elimination enhances the matching speed more than 16x compared to Approximate Nearest Neighbor searching processors. The proposed Vocabulary Forest processor, implemented in 65nm CMOS process, achieves 2.07M-vec/s throughput and 13.3nJ/vector energy efficiency, and successfully matches 100 objects with 95.7% matching accuracy.