文章摘要
余震,何留杰,吴婷.基于融合鲁棒特征与多维尺度变换的紧凑图像哈希算法[J].包装工程,2019,40(1):186-195.
YU Zhen,HE Liu-jie,WU Ting.Compact Image Hash Algorithm Based on Fusion Robust Features and Multidimensional Scaling.Packaging Engineering,2019,40(1):186-195.
基于融合鲁棒特征与多维尺度变换的紧凑图像哈希算法
Compact Image Hash Algorithm Based on Fusion Robust Features and Multidimensional Scaling
投稿时间:2018-08-28  修订日期:2019-01-10
DOI:10.19554/j.cnki.1001-3563.2019.01.029
中文关键词: 图像哈希  融合鲁棒特征  多维尺度变换  双线性插值  YCbCr颜色空间  Fourier变换  残差机制
英文关键词: image hashing  fusion robust features  multidimensional scaling  bilinear interpolation  YCbCr color space  Fourier transform  residual mechanism
基金项目:国家自然科学基金(61379079);河南省国际科技合作基金(144300510007);河南省产学研合作计划(152107000093)
作者单位
余震 1.黄河科技学院郑州 450063 
何留杰 1.黄河科技学院郑州 450063 
吴婷 2.中原工学院郑州 450007 
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中文摘要:
      目的 为了增强哈希序列对任意旋转角度的鲁棒性与识别能力,提出一种基于融合鲁棒特征与多维尺度变换的紧凑图像哈希算法。方法 首先,利用双线性插值来固定图像的哈希序列长度,获取规则尺寸的图像;借助高斯低通滤波对规则图像完成过滤操作,消除噪声污染和插值误差对哈希生成的影响;将滤波图像转换到YCbCr颜色空间,提取亮度Y分量,增强哈希对亮度调整的鲁棒性;利用极坐标变换LPT方法处理亮度Y分量,输出二次图像;引入SVD机制来分解二次图像,获取其抗旋转的鲁棒特征;同时,根据Fourier变换与残差机制,获取Y分量的局部显著特征;随后,将这2种特征组合,形成融合鲁棒特征,将其视为中间哈希序列;引入多维尺度变换,对中间哈希序列完成压缩,获取紧凑哈希;基于Logistic映射,完成紧凑哈希序列的加密,形成目标哈希;通过计算真实图像与待认证图像之间哈希序列对应的Hamming距离,根据预设阈值,完成图像识别。结果 测试数据表明,较已有的哈希方案而言,所提方案拥有更高的鲁棒性和更紧凑的哈希长度,呈现出更为理想的ROC曲线,在多种攻击下,其稳定的正确识别率保持在96%以上。结论 所提哈希方案拥有良好的鲁棒性与敏感性,在包装图标检索、信息水印等行业具备较好的应用价值。
英文摘要:
      The work aims to propose a compact image hash algorithm based on fusion robust features and multidimensional scaling transform, in order to enhance the robustness and recognition ability of hash sequences for arbitrary rotation angles. Firstly, bilinear interpolation was used to fix the hash sequence length of the image for obtaining images of regular size. The Gauss low-pass filtering was used to filter regular images to eliminate the influence of noise pollution and interpolation error on the hash generation. Then, the filtered image was transformed into YCbCr color space for extracting the brightness Y component, so as to enhance the hash robustness with brightness adjustment. Then, the log-polar transform LPT was used to process the brightness Y component for outputting the secondary image. The SVD mechanism was introduced to decompose the secondary image for obtaining the robust features of its anti-rotation. At the same time, the local salient features of the Y component were obtained based on Fourier transform and residual mechanism. Subsequently, the two features were combined to form a fusion robust feature, which was regarded as an intermediate hash sequence. The multidimensional scaling was introduced to compress the intermediate hash sequence for obtaining compact hash. The compact hash sequence was encrypted base on Logistic map to form the target hash. By calculating the Hamming distance of hash sequence between the real image and the image to be authenticated, the image recognition was determined according to the preset threshold. Experimental results showed that, the proposed algorithm had stronger robustness and more compact hash length, as well as more ideal ROC curve, compared with the existing hash scheme, and its correct recognition rate of stability was over 96% under a variety of attacks. Featured by good robustness and sensitivity, the proposed hash scheme has better application value in packaging icon retrieval, information watermarking and other industries.
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