Aiming at the problem that two-dimensional code is prone to motion blur in industrial product detec- tion ,resulting in increased recognition difficulty ,a motion blur two-dimensional code image restoration method based on improved Wiener filter is designed. In the traditional Wiener filter image restoration process ,due to the influence of the regular term K value ,resulting in the difference in the restoration effect ,this paper combines the genetic algo- rithm ,through the adaptive optimization method to achieve the estimation of K value ,the experimental results show that the improved algorithm is about 4 dB higher than the traditional algorithm restored image peak signal-to-noise ra- tio ( PSNR) ,the method can effectively restore the motion blur two-dimensional code image ,improve the efficiency of two-dimensional code recognition.