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A fast feature selection for cotton foreign fiber objects based on binary particle swarm optimization was presented, for the current feature selection of cotton foreign fiber having more iteration times and slow speed. Binary particle swarm optimization (BPSO) was used to select feature in the method, and the support vector machine algorithm was used to verify the optimal feature set. Experimental results showed that the running time could reduce by 26%, when the classification accuracy was almost with other algorithms.