JOURNAL OF SHANDONG UNIVERSITY(NATURAL SCIENCE) ›› 2026, Vol. 61 ›› Issue (3): 11-19.doi: 10.6040/j.issn.1671-9352.9.2025.003

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Forensic analysis of poster design infringement based on visual salient features

YANG Bin1, SUN Jiannan1, CAO Enguo1*, LI Zichuan2, ZHOU Zhili3   

  1. 1. School of Digital Technology&
    Innovation Design, Jiangnan University, Wuxi 214122, Jiangsu, China;
    2. School of Public Security Information Technology and Information, Criminal Investigation Police University of China, Shenyang 110854, Liaoning, China;
    3. Institute of Artificial Intelligence, Guangzhou University, Guangzhou 511363, Guangdong, China
  • Published:2026-03-18

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Abstract: Traditional clone detection methods primarily rely on pixel-level image similarities, often overlooking conceptual similarities in core design elements, particularly in compositional layouts. To address this limitation, we propose a forensic method for detecting poster design infringement based on visual saliency features, aimed at assisting experts in identifying and assessing conceptual plagiarism. To achieve this goal, a sophisticated deep learning model comprising four sub-networks is developed to process complex visual elements in design works and explicitly delineate key layout structural relationships. By computing conceptual feature similarities between posters and existing works, proposed method effectively identifies designers infringing behaviors. The experimental results demonstrate significant improvements in accuracy compared to traditional approaches in poster design infringement forensic analysis.

Key words: image processing, similarity calculation, visual saliency, plagiarism detection, infringement evidence collection

CLC Number: 

  • TP309
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