Deconvolution of the Two-Dimensional Bar Code Based on Binary Constraint

The density of the two-dimensional bar code is high, so the signal is easy to be blurred by the point spread function of the optical system. In order to deblur the image, a novel bar code deconvolution algorithm rooted in binary constraint is proposed in this paper. First, the bar code is rotated to be horizontal using the bilinear interpolation. After analyzing the waveform, the system identification is accomplished. At last, the bar code waveform is reconstructed based on binary constraint. The results show that the performance of the algorithm proposed here is excellent. It can achieve higher recognition rates than previous models.