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A Simple Algorithm for Quickly Estimating the Sharpness of Mobile Phone Images

Published: 28 September 2021 Publication History

Abstract

The QR code image based on halftone micro-noise information, which has excellent anti-duplication performance and certain application value in the field of anti-counterfeiting and traceability. However, due to the mocro-size of halftone noise dots, it's often difficult to obtain high-sharpness images during the recognition process of ordinary mobile phones. In order to obtain high-sharpness halftone QR code images, this paper proposes the improved algorithm of least squares, which can quickly evaluate the sharpness of the scanned image by calculating the gray gradient of local pixels, and proposes PWM algorithm to evaluate the halftone QR code image after segmentation by calculating the proportion of the local high-frequency components. Proved by experiments, the methods in this paper with less time complexity can effectively improve the sharpness of obtained halftone QR code images.

References

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Liu Zhecan. Research on information hiding algorithm based on halftone screening [D]. Beijing: Beijing University of printing, 2014
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Wang Xuan. Research on fast extraction algorithm and application of microstructure information from halftone image [D]. Beijing University of printing, 2019
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Jianbo Chen, Peng Cao, Dazhong Mu, Jianhua Hu, Muming Li, Jing Wang. The Compatibility Study of Recognition Halftone Microstructure Information on Mobile phone[C], Beijing, ICCSIP2016,062.
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DSIT 2021: 2021 4th International Conference on Data Science and Information Technology
July 2021
481 pages
ISBN:9781450390248
DOI:10.1145/3478905
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 28 September 2021

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Author Tags

  1. Halftone Noise Dots
  2. Image Sharpness Evaluation
  3. Least Squares
  4. Local Pixels
  5. PWM

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  • Research-article
  • Research
  • Refereed limited

Funding Sources

  • Beijing Foundation-Municipal Education Commission Joint Project
  • School-level project of Beijing Institute of Graphic Communication

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DSIT 2021

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Overall Acceptance Rate 114 of 277 submissions, 41%

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