研究了基于傅立叶变换的二维条码识别技术.首先探讨了二维条码的定位分割技术，即在条码中分割出单行码字符号的图象，分析条码信号经过点扩展函数卷积后的降质模型，并讨论条码信号的一阶导数和中点的性质，通过分析条码信号，提出了一种计算点扩展函数标准方差的算法 ;然后利用傅立叶变换对条码信号进行反模糊滤波 ;最后对复原的条码信号做差分处理，并采用边界强度直方图策略自适应地选取阈值滤去噪声导致的无效边界.在边界强度直方图中，采用基于矩阈值选取的方法寻找最佳阈值.实验结果表明，该识别算法具有优秀的性能，显著地提高了条码的识别率，满足了实际使用的要求

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.