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.
Highlights
Mobile robots are widely used in indoor environments[1] and two-dimensional (2D) barcodes are popular for robots to detect and peruse the information.[2]
Higher decoding accuracy: The format information of BR code is stored with blur-invariant geometric features, which can be retrieved correctly in a severely blurred image
To solve the problems of recognition rate decline and decoding failure for 2D barcode under defocus blur, the blur-invariant shape and geometric features are derived, and a BR code based on these features is presented
Summary
Mobile robots are widely used in indoor environments[1] and two-dimensional (2D) barcodes are popular for robots to detect and peruse the information.[2]. Blur invariant is based on the idea of direct analysis of the degraded blurry images.[14,22,23] A large number of related articles using this concept have been published.[24] In this article, we try to find out the shape and geometric features that are invariant to blur and used them to make up a blur-readable (BR) 2D barcode that can be decoded without deblurring It is focused on the application scenario of low-speed robot and defocus blur is a main factor reducing the quality of captured images. The finder patterns of the ordinary 2D barcode cannot be located in a severely blurred image
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