Harris算子耦合强度特征的图像复制-粘贴篡改检测算法
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摘要
目的针对当前较多图像复制-粘贴篡改检测算法主要依靠度量图像的结构特征来实现篡改检测,忽略了图像的强度特征,使其在各种几何变换下难以准确检测出伪造内容,导致检测结果中存在漏检和误检等问题,设计一种基于Harris算子耦合强度特征的图像复制-粘贴篡改检测算法。方法利用Harris算子对图像的特征点进行精确的提取。通过特征点构造圆形特征区域,求取该区域的Zernike矩,通过Zernike矩的大小实现对特征点的描述。随后,利用不同阶数的Zernike矩来描述图像的强度特征和纹理特征,从而构造匹配模型,对图像特征进行粗匹配,并引入RANSAC方法对粗匹配结果进行优化。最后,利用形态学腐蚀与膨胀操作将特征区域进行连通,以确定篡改区域。结果实验结果表明,与已有的图像伪造检测方案相比,所提算法具备更高的检测精度和鲁棒性,在噪声和旋转等变换下仍有更好的检测效果。结论所提技术拥有较高的伪造检测准确性,在图像水印、信息安全领域具有一定的参考价值。
The work aims to design an image copy-move forgery detection algorithm based on Harris operator coupling intensity to solve the problem that most existing copy-and-paste tamper detection algorithms mainly rely on measuring the structural characteristics of the image to achieve tamper detection, thus ignoring the image strength characteristics,making the algorithm can not adapt to rotation and other tamper detection methods, resulting in the detection results of leakage detection and error detection. The Harris operator was used to extract the feature points accurately. A circular feature region was constructed by feature points, and the Zernike moments of the region were obtained. The feature points were described by the size of the Zernike moments. Zernike moments of different orders were used to describe the intensity and texture features of the image. The matching model was constructed by the size of Zernike moments of different orders to roughly match the image features. The RANSAC method was introduced to further realize the precise matching of image features. The feature area was connected by morphological corrosion and expansion operation to determine the tampering area. From the experimental results, the proposed algorithm had high detection accuracy and roughness and still had better detection results under the noise and rotation, compared with the existing image forgery detection scheme. The proposed technique possesses high forgery detection accuracy and has certain reference value in the fields of image watermarking and information security.
The work aims to design an image copy-move forgery detection algorithm based on Harris operator coupling intensity to solve the problem that most existing copy-and-paste tamper detection algorithms mainly rely on measuring the structural characteristics of the image to achieve tamper detection, thus ignoring the image strength characteristics,making the algorithm can not adapt to rotation and other tamper detection methods, resulting in the detection results of leakage detection and error detection. The Harris operator was used to extract the feature points accurately. A circular feature region was constructed by feature points, and the Zernike moments of the region were obtained. The feature points were described by the size of the Zernike moments. Zernike moments of different orders were used to describe the intensity and texture features of the image. The matching model was constructed by the size of Zernike moments of different orders to roughly match the image features. The RANSAC method was introduced to further realize the precise matching of image features. The feature area was connected by morphological corrosion and expansion operation to determine the tampering area. From the experimental results, the proposed algorithm had high detection accuracy and roughness and still had better detection results under the noise and rotation, compared with the existing image forgery detection scheme. The proposed technique possesses high forgery detection accuracy and has certain reference value in the fields of image watermarking and information security.
引文
[1]SOMAYEH S,SAJJAD D,HAMID A J.State of the Art in Passive Digital Image Forgery Detection:Copy-Move Image Forgery[J].Pattern Analysis and Applications,2018,21(2):291-306.
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[9]EMAM M,HAN Q,ZHANG Hong-li.Two-Stage Keypoint Detection Scheme for Region Duplication Forgery Detection in Digital Images[J].Journal of Forensic Sciences,2018,63(1):102-111.
[10]ZAINEB B,HAKIM E F,KHALID Z.Exact Zernike and Pseudo-Zernike Moments Image Reconstruction Based on Circular Overlapping Blocks and Chamfer Distance[J].Signal,Image and Video Processing,2017,11(7):1313-1320.
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[12]杨兴宇,阮怀林.基于Zernike矩和双谱特征的新型干扰识别算法[J].空军工程大学学报(自然科学版),2018,19(2):56-61.YANG Xing-yu,RUAN Huai-lin.Jamming Identification Algorithms of Advanced Jamming Based on Bispecturm Feature and Zernike Moment[J].Journal of Air Force Engineering University(Natural Science Edition),2018,19(2):56-61.
[13]OUYANG Jun-lin,LIU Yi-zhi,SHU Hua-zhong.Robust Hashing for Image Authentication Using SIFT Feature and Quaternion Zernike Moments[J].Multimedia Tools and Applications,2017,76(2):2609-2626.
[14]DONG Li,MA Hao-tong,PENG Qi.Defocused Spatial Diversity Technology with Aperture Scanning for Aberration Detection and Image Restoration in Aberrated Imaging Systems[J].Optical Engineering,2018,57(8):1-9.
[15]LI Lin,YANG Fan,ZHU Hai-hong.An Improved RANSAC for 3D Point Cloud Plane Segmentation Based on Normal Distribution Transformation Cells[J].Remote Sensing,2017,9(5):1-16.
[16]LI Fan,LIU Shan-shan.A Sub-Region Image Registration Algorithm With Weight-Based Hierarchical Importance Sample Consensus for Moving Target Detection[J].The Imaging Science Journal,2017,65(2):87-97.
[17]SEBASIAN S C,RAMOS-ARREGUíN J M.Image Dehazing Using Morphological Opening,Dilation and Gaussian Filtering[J].Signal,Image and Video Processing,2018,12(7):1329-1335.
[18]SONG Bin,BAIK D K,ZHOU Shun-xian.Human Eye Location Algorithm Based on Multi-Scale Self-Quotient Image and Morphological Filtering for Multimedia Big Data[J].Multimedia Tools and Applications,2018,77(8):10063-10075.
[19]DANIEL C J,CAMPBELL-BORGES Y C,SANTOS-COELHO L D.Image Forgery Detection By Semi-automatic Wavelet Soft-thresholding With Error Level Analysis[J].Expert Systems with Applications,2017,85(1):348-356.
[20]陈辉映,张大兴,杨珊珊.基于SURF的图像多区域复制粘贴篡改检测[J].计算机工程与设计,2018,39(8):2593-2597.CHEN Hui-ying,ZHANG Da-xing,YANG Shan-shan.Image Multiple Copy-Move Forgery Detection Based on SURF Algorithm[J].Computer Engineering and Design,2018,39(8):2593-2597.
[2]REBINA E J,KOUSALYS G.Spectral-Hashing-Based Image Retrieval and Copy-Move Forgery Detection[J].Australian Journal of Forensic Sciences,2016,48(6):643-658.
[3]JINSEOK P,DAIKYUNG H,JONGUK H.Detecting Digital Image Forgery in Near-Infrared Image of CCTV[J].Multimedia Tools and Applications,2017,76(14):15817-15838.
[4]OUSSAMA B,HOUCEMEDDINE H.Chaotic Watermark for Blind Forgery Detection in Images[J].Multimedia Tools and Applications,2016,75(14):8659-8718.
[5]HU W C,CHEN W H,HUANG D Y.Effective Image Forgery Detection of Tampered Foreground or Background Image Based on Image Watermarking and Alpha Mattes[J].Multimedia Tools and Applications,2016,75(6):3495-3516.
[6]ALAHMADI A,HUSSAIN M,ABOALSAMH H.Passive Detection of Image Forgery Using DCT and Local Binary Pattern[J].Signal,Image and Video Processing,2017,11(1):81-88.
[7]林开司,张安东,张志宏.基于图像锐化的SIFT图像复制粘贴篡改检测[J].齐齐哈尔大学学报(自然科学版),2018,34(1):33-36.LIN Kai-si,ZHANG An-dong,ZHANG Zhi-hong.SIFT Image Copy-Paste Tamper Detection Based on Image Sharpening[J].Journal of Qiqihar University(Natural Science Edition),2018,34(1):33-36.
[8]陈青,孙彦飞,郭功勋.基于Harris角点的抗几何攻击数字水印算法研究[J].包装工程,2018,39(13):188-193.CHEN Qing,SUN Yan-fei,GUO Gong-xun.Digital Watermarking Algorithm Resistant to Geometric Attacks Based on Harris Corner[J].Packaging Engineering,2018,39(13):188-193.
[9]EMAM M,HAN Q,ZHANG Hong-li.Two-Stage Keypoint Detection Scheme for Region Duplication Forgery Detection in Digital Images[J].Journal of Forensic Sciences,2018,63(1):102-111.
[10]ZAINEB B,HAKIM E F,KHALID Z.Exact Zernike and Pseudo-Zernike Moments Image Reconstruction Based on Circular Overlapping Blocks and Chamfer Distance[J].Signal,Image and Video Processing,2017,11(7):1313-1320.
[11]BUDIMIR L,MILOS D,SRDJAN S.An Algorithm for Robust Image Watermarking Based on the DCT and Zernike Moments[J].Multimedia Tools and Applications,2017,76(22):23333-23352.
[12]杨兴宇,阮怀林.基于Zernike矩和双谱特征的新型干扰识别算法[J].空军工程大学学报(自然科学版),2018,19(2):56-61.YANG Xing-yu,RUAN Huai-lin.Jamming Identification Algorithms of Advanced Jamming Based on Bispecturm Feature and Zernike Moment[J].Journal of Air Force Engineering University(Natural Science Edition),2018,19(2):56-61.
[13]OUYANG Jun-lin,LIU Yi-zhi,SHU Hua-zhong.Robust Hashing for Image Authentication Using SIFT Feature and Quaternion Zernike Moments[J].Multimedia Tools and Applications,2017,76(2):2609-2626.
[14]DONG Li,MA Hao-tong,PENG Qi.Defocused Spatial Diversity Technology with Aperture Scanning for Aberration Detection and Image Restoration in Aberrated Imaging Systems[J].Optical Engineering,2018,57(8):1-9.
[15]LI Lin,YANG Fan,ZHU Hai-hong.An Improved RANSAC for 3D Point Cloud Plane Segmentation Based on Normal Distribution Transformation Cells[J].Remote Sensing,2017,9(5):1-16.
[16]LI Fan,LIU Shan-shan.A Sub-Region Image Registration Algorithm With Weight-Based Hierarchical Importance Sample Consensus for Moving Target Detection[J].The Imaging Science Journal,2017,65(2):87-97.
[17]SEBASIAN S C,RAMOS-ARREGUíN J M.Image Dehazing Using Morphological Opening,Dilation and Gaussian Filtering[J].Signal,Image and Video Processing,2018,12(7):1329-1335.
[18]SONG Bin,BAIK D K,ZHOU Shun-xian.Human Eye Location Algorithm Based on Multi-Scale Self-Quotient Image and Morphological Filtering for Multimedia Big Data[J].Multimedia Tools and Applications,2018,77(8):10063-10075.
[19]DANIEL C J,CAMPBELL-BORGES Y C,SANTOS-COELHO L D.Image Forgery Detection By Semi-automatic Wavelet Soft-thresholding With Error Level Analysis[J].Expert Systems with Applications,2017,85(1):348-356.
[20]陈辉映,张大兴,杨珊珊.基于SURF的图像多区域复制粘贴篡改检测[J].计算机工程与设计,2018,39(8):2593-2597.CHEN Hui-ying,ZHANG Da-xing,YANG Shan-shan.Image Multiple Copy-Move Forgery Detection Based on SURF Algorithm[J].Computer Engineering and Design,2018,39(8):2593-2597.