基于显著性特征的海报设计侵权检测分析

Forensic analysis of poster design infringement based on visual salient features

摘要

为辅助专家进行概念侵权行为的检测与判定,本文提出一种基于视觉显著性特征的海报设计侵权行为取证方法。提出设计了一个包含4个子网络的复杂深度学习模型,用于处理设计作品中的复杂视觉元素,并明确地划分出主要的版式结构关系。通过计算海报与现有作品之间的相似度,本方法能有效检测出设计师的侵权行为。实验结果显示,本方法在海报设计侵权行为取证分析上的准确率较传统方法有显著提升。

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 designer̓s infringing behaviors. The experimental results demonstrate significant improvements in accuracy compared to traditional approaches in poster design infringement forensic analysis.

关键词

图像处理 / 相似度计算 / 视觉显著性 / 抄袭检测 / 侵权行为取证

Key words

image processing / similarity calculation / visual saliency / plagiarism detection / infringement evidence collection

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基金资助

国家自然科学基金资助项目(21BG131)

江苏高校哲学社会科学研究重大资助项目(2025SJZD110)

辽宁网络安全执法协同创新中心资助项目()