• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Information Forensics and Security, IEEE Transactions on >Fragility Analysis of Adaptive Quantization-Based Image Hashing
【24h】

Fragility Analysis of Adaptive Quantization-Based Image Hashing

机译：基于自适应量化的图像哈希的脆弱性分析

获取原文
获取原文并翻译 | 示例
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

Fragility is one of the most important properties of authentication-oriented image hashing. However, to date, there has been little theoretical analysis on the fragility of image hashing. In this paper, we propose a measure called expected discriminability for the fragility of image hashing and study this fragility theoretically based on the proposed measure. According to our analysis, when Gray code is applied into the discrete-binary conversion stage of image hashing, the value of the expected discriminability, which is dominated by the quantization stage of image hashing, is no more than 1/2. We further evaluate the expected discriminability of the image-hashing scheme that uses adaptive quantization, which is the most popular quantization scheme in the field of image hashing. Our evaluation reveals that if deterministic adaptive quantization is applied, then the expected discriminability of the image-hashing scheme can reach the maximum value (i.e., 1/2). Finally, some experiments are conducted to validate our theoretical analysis and to compare the performance of several quantization schemes for image hashing.
机译：脆弱性是面向身份验证的图像哈希的最重要属性之一。但是，迄今为止，关于图像哈希的脆弱性的理论分析很少。在本文中，我们针对图像哈希的脆弱性提出了一种称为“预期可辨性”的措施，并在此提议的基础上从理论上研究了这种脆弱性。根据我们的分析，当格雷码应用于图像哈希的离散二进制转换阶段时，以图像哈希的量化阶段为主的预期可分辨性的值不超过1/2。我们进一步评估了使用自适应量化的图像哈希方案的预期可分辨性，自适应量化是图像哈希领域中最流行的量化方案。我们的评估表明，如果应用确定性自适应量化，则图像哈希方案的预期可辨别性可以达到最大值（即1/2）。最后，进行了一些实验以验证我们的理论分析并比较几种用于图像哈希的量化方案的性能。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号