Revealing the Trace of High-Quality JPEG Compression through Quantization Noise Analysis

   December 11, 2017    Comments Off on Revealing the Trace of High-Quality JPEG Compression through Quantization Noise Analysis    Posted in: IEEE 2017, MATLAB

Revealing the Trace of High-Quality JPEG Compression Through Quantization Noise Analysis

ABSTRACT:

To identify whether an image has been JPEG compressed is an important issue in forensic practice. The state-of-the-art methods fail to identify high-quality compressed images, which are common on the Internet. In this paper, we provide a novel quantization noise-based solution to reveal the traces of JPEG compression. Based on the analysis of noises in multiple-cycle JPEG compression, we define a quantity called forward quantization noise. We analytically derive that a decompressed JPEG image has a lower variance of forward quantization noise than its uncompressed counterpart. With the conclusion, we develop a simple yet very effective detection algorithm to identify decompressed JPEG images. We show that our method outperforms the state-of-the-art methods by a large margin especially for high-quality compressed images through extensive experiments on various sources of images. We also demonstrate that the proposed method is robust to small image size and chroma subsampling. The proposed algorithm can be applied in some practical applications, such as Internet image classification and forgery detection.

 

EXISTING SYSTEM:

  • Traces of JPEG compression may also be found in the histogram of DCT coefficients. Luo et al. noted that JPEG compression reduces the amount of DCT coefficients with an absolute value no larger than one. There are less DCT coefficients in the range of [−1,1] after JPEG compression. A discriminative statistics based on measuring the amount of DCT coefficients in the range of [−2,2] is constructed. When the statistics of a test image exceeds a threshold, it is classified as uncompressed. Otherwise, it is identified as having been previously JPEG compressed.
  • Although Luoet al.’s method is considered as the current state of the art in terms of its identification performance, it has a few shortcomings. First, the analysis only uses a portion of the DCT coefficients that are close to 0. Hence, information is not optimally utilized. Second, the method requires the quantization step to be no less than 2 to be effective. As a result, this method fails on high-quality compressed image such as those with a quantization table containing mostly quantization steps being ones.

 

DISADVANTAGES OF EXISTING SYSTEM:

  • High quality compression is not achieved.
  • Existing method fails on high-quality compressed image such as those with a quantization table containing mostly quantization steps being ones.

 

PROPOSED SYSTEM:

  • In this paper, we focus on the problem of identifying whether an image currently in uncompressed form is truly uncompressed or has been previously JPEG compressed. Being able to identify such a historical record may help to answer some forensics questions related to the originality and the authenticity of an image, such as where is the image coming from, whether it is an original one, or whether any tampering operation has been performed.
  • In this paper, we propose a method to reveal the traces of JPEG compression. The proposed method is based on analyzing the forward quantization noise, which is obtained by quantizing the block-DCT coefficients with a step of one. A decompressed JPEG image has a lower noise variance than its uncompressed counterpart. Such an observation can be derived analytically.
  • The main contribution of this work is to address the challenges posed by high-quality compression in JPEG compression identification. Specifically, our method is able to detect the images previously compressed with IJG QF=99 or 100, and Photoshop QF from 90 to 100.

 

ADVANTAGES OF PROPOSED SYSTEM:

  • Show that high-quality compressed images.
  • Experiments show that high-quality compressed images are common on the Internet, and our method is effective to identify them. Besides, our method is robust to small image size and color sub-sampling in chrominance channels.
  • The proposed method can be applied to Internet image classification and forgery detection with relatively accurate results.
  • We show that our method outperforms the previous methods by a large margin for high-quality JPEG compressed images which are common on the Internet and present a challenge for identifying their compression history.

SYSTEM ARCHITECTURE:

SYSTEM REQUIREMENTS:

HARDWARE REQUIREMENTS:

 

  • System : Pentium IV 2.4 GHz.
  • Hard Disk : 40 GB.
  • Floppy Drive : 44 Mb.
  • Monitor : 15 VGA Colour.
  • Mouse :
  • Ram : 512 Mb.

SOFTWARE REQUIREMENTS:

 

  • Operating system : Windows XP/7.
  • Coding Language : MATLAB
  • Tool : MATLAB R2013A

 

REFERENCE:

Bin Li, Member, IEEE, Tian-Tsong Ng, Xiaolong Li, Shunquan Tan, Member, IEEE, and Jiwu Huang, Senior Member, IEEE, “Revealing the Trace of High-Quality JPEG Compression Through Quantization Noise Analysis”, IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY, VOL. 10, NO. 3, MARCH 2015.

  

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