Two-dimensional bar code out-of-focus deblurring via the Increment Constrained Least Squares filter

When a two-dimensional bar code is away from a camera’s focus, the image is blurred by the convolution of the point spread function. In the presence of noise, the out-of-focus deblurring is an ill-posed problem. The two-dimensional bar code image has a very special form, making deblurring feasible. This paper proposes a fast deblurring algorithm called the Increment Constrained Least Squares filter that is specifically designed for two-dimensional bar code images. After analyzing the bar code image, the standard deviation of the Gaussian blur kernel is obtained. Then, the bar code image is restored through on iterative computations. In each iteration, the bi-level constraint of the bar code image is efficiently incorporated. Experimental results show that our algorithm can obtain better bar code image quality compared with existing methods. Our method can also improve the reading depth of field, which is an important performance parameter for bar code readers.

► We design a fast deblurring algorithm specifically for two-dimensional bar codes.
► The bi-level constraint is efficiently incorporated in each iteration of the algorithm.
► The algorithm can obtain better image quality under the influence of noise.
► The algorithm successfully improves the reading depth of field of bar code readers.