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

  • Authors:

  • Ningzhong Liu;Xingming Zheng;Han Sun;Xiaoyang Tan

  • Affiliations:

  • College of Computer Science & Technology, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China;College of Computer Science & Technology, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China;College of Computer Science & Technology, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China;College of Computer Science & Technology, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China

  • Venue:
  • Pattern Recognition Letters
  • Year:
  • 2013

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Abstract

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.