基于像素缩放残差的块效应的图像局部变形检测方法
Image Local Deformation Detection Method Based on Block Effect of Pixel Scaling Residual
DOI: 10.12677/CSA.2019.97145, PDF,   
作者: 王瑞昆:天津工业大学计算机科学与技术学院,天津
关键词: 图像缩放BAGJPEG图像局部变形图像取证Image Scaling BAG JPEG Local Image Deformation Image Forensics
摘要: 将篡改图像用于不合法的途径会侵害公民的知情权、肖像权等领域,图像的局部变形常用在对图像中人物进行瘦身瘦脸等操作,本文提出一种检测jpeg压缩图像的局部变形篡改操作的改进方法,能够更好的检测图像局部变形的位置。首先对待检测图像使用1像素缩放的方法提取其残差图像,之后对残差图像提取周期为8的块效应网格,之后依据块效应网格的不一致性来检测图像局部变形的位置,其中在检测块效应的不一致性时,我们使用了新的特征。经过实验表明我们提出的方法改进了原有块效应的检测结果。
Abstract: The use of tampered images in illegal ways will infringe citizens’ right to know and portrait. Local distortion of images is often used in image thinning operations. This paper proposes an improved method to detect local distortion of JPEG compressed images, which can better detect the location of local distortion of images. Firstly, the residual image of the detected image is extracted by one-pixel scaling method, and then the block-effect mesh with a period of 8 is extracted from the residual image. Then, the location of the local distortion of the image is detected according to the inconsistency of the block-effect mesh. In detecting the inconsistency of the block-effect, we use new features. Experiments show that the proposed method improves the detection results of the original block effect.
文章引用:王瑞昆. 基于像素缩放残差的块效应的图像局部变形检测方法[J]. 计算机科学与应用, 2019, 9(7): 1288-1295. https://doi.org/10.12677/CSA.2019.97145

参考文献

[1] Kee, E. and Farid, H. (2011) A Perceptual Metric for Photo Retouching. Proceedings of the National Academy of Sciences of the United States of America, 108, 19907-19912. [Google Scholar] [CrossRef] [PubMed]
[2] Bharati, A., Singh, R., Vatsa, M. and Bow-yer, K.W. (2016) Detecting Facial Retouching Using Supervised Deep Learning. IEEE Transactions on Information Forensics and Security, 11, 1903-1913. [Google Scholar] [CrossRef
[3] Hwang, M.G., Kim, S.M. and Har, D.H. (2017) A Method of Identifying Digi-tal Images with Geometric Distortion. Australian Journal of Forensic Sciences, 49, 93-105. [Google Scholar] [CrossRef
[4] Fu, D., Shi, Y.Q. and Su, W. (2007) A Generalized Benford’s Law for JPEG Coefficients and Its Applications in Image Forensics. Conference on Security Steganography and Watermarking of Multimedia Contents, 65051L. [Google Scholar] [CrossRef
[5] Yang, J., Xie, J., Zhu, G., Kwong, S. and Shi, Y. (2014) An Effective Method for De-tecting Double JPEG Compression With the Same Quantization Matrix. IEEE Transactions on Information Forensics and Security, 9, 1933-1942. [Google Scholar] [CrossRef
[6] Bianchi, T. and Piva, A. (2012) Detection of Nonaligned Double JPEG Com-pression Based on Integer Periodicity Maps. IEEE Transactions on Information Forensics and Security, 7, 842-848. [Google Scholar] [CrossRef
[7] Pasquini, C., Boato, G. and Perezgonzalez, F. (2014) Multiple JPEG Compres-sion Detection by Means of Benford-Fourier Coefficients. International Workshop on Information Forensics and Security, Atlanta, 3-5 December 2014, 113-118. [Google Scholar] [CrossRef
[8] Fan, Z. and De Queiroz, R.L. (2003) Identification of Bitmap Compression History: JPEG Detection and Quantizer Estimation. IEEE Transactions on Image Processing, 12, 230-235. [Google Scholar] [CrossRef
[9] Li, W., Yuan, Y. and Yu, N. (2009) Passive Detection of Doctored JPEG Image via Block Artifact Grid Extraction. Signal Processing, 89, 1821-1829. [Google Scholar] [CrossRef
[10] Christlein, V., Riess, C., Jordan, J. and Angelopoulou, E. (2012) An Evaluation of Popular Copy-Move Forgery Detection Approaches. IEEE Transactions on Information Forensics and Security, 7, 1841-1854. [Google Scholar] [CrossRef