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A quality detection is an important process in the production line of electric machinery commutator. The inspecting mode still dependent on human, leads low speed of detection and low accuracy. A system for on-line inspection quality of electric machinery commutator is developed using a machine vision technology. Aiming at the problems where exists different inspecting standards of commutator shape because of the production process, an approach of adaptive learning templet to detect the shape is proposed. An improved method to detect the diameter of axle hole is based on Freeman chain code. Aimming to defect flaw of end-surface of commutator, an approach based on a vision-attention model is proposed. Experimental results show that inspection accuracy of the proposed system reaches 99.80%, miss rate of 0%, and the F - measure value of 99.89%. The system can quickly and effectively detect appearance quality of the commutator, which can meet the needs of the commutator line quality inspection .