Abstract
Barcode image deblurring has been an important task in image processing domain. On production lines, the demand of using 2D barcode to identify moving products requires scanners to decode the blurred images efficiently. Therefore, a fast and robust deblurring method is needed. However, most of state-of-the-art methods are not suitable for the fast decoding of 2D barcode images due to their being time-consuming. In this paper, we propose an efficient deblurring method for 2D barcode image focusing on linear motion blur in manufacturing situations. We first deconvolute image with Wiener Filter. Then we form a metrics which is based on the binary property of 2D barcode image to evaluate the quality of each deblurred image. With the guide of this metrics, we adopt a line-search method to reduce the time spent on searching the best blur kernel. We compare our method with the existing methods for 2D barcode regarding efficiency and effectiveness. The experiment results show that our method is much faster on recovering information from motion-blurred 2D barcode.
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