caa a22 4500 605541094 CHVBK 20210128100914.0 cr unu---uuuuu 210128e20150601xx s 000 0 eng 10.1007/s00371-015-1107-x doi (NATIONALLICENCE)springer-10.1007/s00371-015-1107-x Structure-aware QR Code abstraction [Elektronische Daten] [Siyuan Qiao, Xiaoxin Fang, Bin Sheng, Wen Wu, Enhua Wu] Quick Response Codes (QR Codes) have proved to be a great success in both automotive industry and general commercial use. However, in most cases, QR Codes are not identified as aesthetical, since the original motivation to invent QR Codes is to achieve high speed and high readability in scanning. This paper proposes a solution framework for QR Code abstraction, which produces machine readable QR Code that is visually similar to the input image. Unlike the existing schemes for QR Code abstraction, which produces QR Codes of low resolution, the framework aims to resolve the high computation complexity of producing halftone QR Codes of high resolution with both similarity and readability preserved. The solution framework has been implemented and tested on various input texts and images, and a user study was conducted to evaluate its performance in preserving similarity. The experimental results show that the framework can produce QR Codes of high resolution and high similarity without compromising readability. Springer-Verlag Berlin Heidelberg, 2015 QR Code abstraction nationallicence Structure-aware halftoning nationallicence Parallel computing nationallicence Qiao Siyuan Department of Computer Science and Engineering, Shanghai Jiao Tong University, Shanghai, China aut Fang Xiaoxin Department of Computer Science and Engineering, Shanghai Jiao Tong University, Shanghai, China aut Sheng Bin Department of Computer Science and Engineering, Shanghai Jiao Tong University, Shanghai, China aut Wu Wen Department of Computer and Information Science, Faculty of Science and Technology, University of Macau, Macao, China aut Wu Enhua State Key Laboratory of Computer Science, Institute of Software, Chinese Academy of Sciences, Beijing, China aut The Visual Computer Springer Berlin Heidelberg 31/6-8(2015-06-01), 1123-1133 0178-2789 31:6-8<1123 2015 31 371 https://doi.org/10.1007/s00371-015-1107-x text/html Onlinezugriff via DOI BK010053 XK010053 XK010000 Metadata rights reserved Springer special CC-BY-NC licence nationallicence 1 research-article jats NATIONALLICENCE NATIONALLICENCE NL-springer NATIONALLICENCE 856 40 https://doi.org/10.1007/s00371-015-1107-x text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Qiao Siyuan Department of Computer Science and Engineering, Shanghai Jiao Tong University, Shanghai, China aut NATIONALLICENCE 700 1- Fang Xiaoxin Department of Computer Science and Engineering, Shanghai Jiao Tong University, Shanghai, China aut NATIONALLICENCE 700 1- Sheng Bin Department of Computer Science and Engineering, Shanghai Jiao Tong University, Shanghai, China aut NATIONALLICENCE 700 1- Wu Wen Department of Computer and Information Science, Faculty of Science and Technology, University of Macau, Macao, China aut NATIONALLICENCE 700 1- Wu Enhua State Key Laboratory of Computer Science, Institute of Software, Chinese Academy of Sciences, Beijing, China aut NATIONALLICENCE 773 0- The Visual Computer Springer Berlin Heidelberg 31/6-8(2015-06-01), 1123-1133 0178-2789 31:6-8<1123 2015 31 371