A novel two-dimensional bar code recognition algorithm based on Fourier transform is proposed in this paper. First

the location and segment technology of two-dimensional bar code is discussed and a single row codeword image is obtained. Then the model of blurred bar code signal caused by the point spread function is given. The first derivative and midpoint of bar code signal is discussed. After analyzing the bar code signal

the standard deviation of the point spread function is obtained. The bar code signal is deblurred based on Fourier transform. At last

after getting the first derivative of signal

the edge strength histogram is used to drop invalid edge caused by noise adaptively. In the edge strength histogram

based-moment threshold selection is used to decide the threshold.The experimental results show that the performance of the algorithm proposed in this paper is excellent. It can achieve higher recognition rate of high density bar code

which suffices to the requirement of the practical use.