Computer Science ›› 2021, Vol. 48 ›› Issue (11): 234-241.doi: 10.11896/jsjkx.200900121

• Computer Graphics & Multimedia • Previous Articles     Next Articles

Smoothing Filter Detection Algorithm Based on Middle and Tail Information of Differential Histogram

DAN Zhou-yang, LIU Fen-lin, GONG Dao-fu   

  1. School of Cybersapce Security,Information Engineering University,Zhengzhou 450001,China
  • Received:2020-09-15 Revised:2021-01-11 Online:2021-11-15 Published:2021-11-10
  • About author:DAN Zhou-yang,born in 1996,postgraduate.His main research interests include information security and digital image forensics.
    LIU Fen-lin,born in 1964,Ph.D,professor,Ph.D supervisor.His main research interests include digital image forensics and information hiding.
  • Supported by:
    National Natural Science Foundation of China(61772549,U1736214).

Abstract: Smoothing is an important method for digital image denoising and blurring.It is often used to beautify and retouch “forged” images.Therefore,it is necessary to detect various smoothing filters.Aiming at the common image smoothing proces-sing,this paper proposes a new smoothing filter detection algorithm based on the tail information of differential histogram.Firstly,for the image to be detected,multiple difference absolute value histograms are constructed based on different difference step lengths and directions.Then,the occurrence frequency of the difference values of 0 and 1 in the histogram is extracted,and the several difference values from large to small at the tail of the histogram and their occurrence frequency are extracted to construct multi-dimensional detection feature.Finally,an SVM classifier is constructed to detect images.The experiments of smoothing detection and distinguishing different smoothing filters are carried out on the image library.The experimental results show that the proposed algorithm has excellent detection performance for three common spatial smoothing filters,including median filter,ave-rage filter and Gaussian filter.In addition,the algorithm can effectively distinguish smoothing filter from sharpening,scaling,compression and other digital image operations,and has robustness in JPEG compressed image.

Key words: Difference histogram, Digital image forensics, Smoothing detection, Smoothing filter

CLC Number: 

  • TP391
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