Traditionally, the method of bar code recognition is based on edge detection. Because of the high density of the stacked two-dimensional bar code, the signal is severely blurred by the point spread function of the optical system. And this method is not suitable. In order to deblur the image, a deconvolution technique is necessary. Under the influence of noise, deconvolution is a type of ill-posed problem. Based on the idea of bar codes as bilevel waveforms, a novel bar code recognition algorithm rooted in iterative deconvolution is proposed in this paper. First, the bar code is rotated to be horizontal using the interpolation of sixteen points. After analysing the waveform, the system identification is accomplished. At last, the bar code waveform is reconstructed based on iterative computations. The results show that the performance of the algorithm proposed here is excellent. It can achieve higher recognition rates than previous models.

Myoelectric activity of SO and its response to agonists are decreased in rabbits with chronic cholangitis both in vivo and in vitro.