Blur-readable two-dimensional barcode based on blur-invariant shape and geometric features. (25th March 2021)

• Record Type: Journal Article
• Authors: Xie, Shundao; Tan, Hong-Zhou
• Is Part Of: International journal of advanced robotic systems. Volume 18:Number 2(2021)
• Publication Date: 2021-03-25
• Subjects: Two-dimensional barcode -- blur-invariant shape -- circular disk PSF -- finder patterns -- blur-readable code; Robotics -- Periodicals; Robotics; Periodicals; 629.892
• DOI: 10.1177/1729881421999589
• Languages: English
• ISSNs: 1729-8806

Abstract

In recent years, the application of two-dimensional (2D) barcode is more and more extensive and has been used as landmarks for robots to detect and peruse the information. However, it is hard to obtain a sharp 2D barcode image because of the moving robot, and the common solution is to deblur the blurry image before decoding the barcode. Image deblurring is an ill-posed problem, where ringing artifacts are commonly presented in the deblurred image, which causes the increase of decoding time and the limited improvement of decoding accuracy. In this article, a novel approach is proposed using blur-invariant shape and geometric features to make a blur-readable (BR) 2D barcode, which can be directly decoded even when seriously blurred. The finder patterns of BR code consist of two concentric rings and five disjoint disks, whose centroids form two triangles. The outer edges of the concentric rings can be regarded as blur-invariant shapes, which enable BR code to be quickly located even in a blurred image. The inner angles of the triangle are of blur-invariant geometric features, which can be used to store the format information of BR code. When suffering from severe defocus blur, the BR code can not only reduce the decoding time by skipping the deblurring process but also improve the decoding accuracy. With the defocus blur described by circular disk point-spread function, simulation results verify the performance of blur-invariant shape and the performance of BR code under blurred image situation.