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Created page with '=Image Forensics= This project is about Image Forensics =Introduction= Intro to my project =Background= I will fill in background first intuitively then rigorously ==Intuitive== …'
 
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Image Forensics
Psych 221 Final Project - Matthew Kahane
=Image Forensics=
=Image Forensics=
This project is about Image Forensics
In a forensic analyst's ideal world, the images we see would be faithful representations of what was seen by the camera.  There are situations in which we would like to detect whether an image has been JPEG compressed multiple times.  A doubly JPEG compressed image would indicated that the image has been saved multiple times and is thus more likely to have been tampered with in between the first save (ostensibly by the camera) and the second save (perhaps in photoshop or some other editing software.) Based on the work of Dartmouth Professor Hany Farid (among others), this project attempts to implement code that will detect doubly compressed images. There are a other ways to go about detecting image forgeries.  One is to implement an Expectation/Maximization algorithm that can detect and interpolate a camera's color filter array.  Parts of an image that do not fit in well with the periodic nature of the CFA will come under suspicion as forged.  This project, though, will take advantage of JPEG compression algorithm (and the artifacts it leaves behind) to detect image forgeries.
=Introduction=
=Introduction=
Intro to my project
Let us begin with the ideas behind JPEG compression. 
=Background=
=Background=
I will fill in background first intuitively then rigorously
I will fill in background first intuitively then rigorously
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==Simulating Compression==
==Simulating Compression==
Here is how I simulated Double Compression
Here is how I simulated Double Compression
==Testing for Double Compression===
==Testing for Double Compression==
Here is how I tested for Double Compression
Here is how I tested for Double Compression
=Results=
=Results=
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[Testing_Script]
[Testing_Script]
[Function_Style_Code]
[Function_Style_Code]
Here is a suggested organization for the project write-up.
Introduction - Motivate the problem. More details are required for custom projects.
Methods - Describe your algorithm or approach. Detail any issues or problems that were particularly important. Emphasize the parts of the project that you wrote (instead of ISET or downloaded code). Describe the analysis in enough detail so that someone could understand and repeat your analysis. What data and software did you use? What were the ideas of the algorithm and data analysis?
Results - Organize your results in a good logical order (not necessarily historical order). Include relevant graphs and/or images. Make sure graph axes are labeled. Make sure you draw the reader's attention to the key element of the figure. The key aspect should be the most visible element of the figure or graph. Help the reader by writing a clear figure caption.
Conclusions - Describe what you learned. What worked? What didn't? Why? What would you do if you kept working on the project?
References _ List references. Include links to papers that are online.
Appendix I - Upload source code, some result images, etc, and give a description of each link. In some cases, your acquired data may be too large to store practically. In this case, use your judgement (or consult one of us) and only link the most relevant data. Be sure to describe the purpose of your code and to edit the code for clarity. The purpose of placing the code online is to allow others to verify your methods and to learn from your ideas. It should be possible for someone else to generate result images using your code.
Appendix II - (for groups only) - Work breakdown. Explain how the project work was divided among group members.

Revision as of 23:27, 19 March 2013

Image Forensics Psych 221 Final Project - Matthew Kahane

Image Forensics

In a forensic analyst's ideal world, the images we see would be faithful representations of what was seen by the camera. There are situations in which we would like to detect whether an image has been JPEG compressed multiple times. A doubly JPEG compressed image would indicated that the image has been saved multiple times and is thus more likely to have been tampered with in between the first save (ostensibly by the camera) and the second save (perhaps in photoshop or some other editing software.) Based on the work of Dartmouth Professor Hany Farid (among others), this project attempts to implement code that will detect doubly compressed images. There are a other ways to go about detecting image forgeries. One is to implement an Expectation/Maximization algorithm that can detect and interpolate a camera's color filter array. Parts of an image that do not fit in well with the periodic nature of the CFA will come under suspicion as forged. This project, though, will take advantage of JPEG compression algorithm (and the artifacts it leaves behind) to detect image forgeries.

Introduction

Let us begin with the ideas behind JPEG compression.

Background

I will fill in background first intuitively then rigorously

Intuitive

Here is your intuition

Rigor

Here is your rigor

Methods

Simulating Compression

Here is how I simulated Double Compression

Testing for Double Compression

Here is how I tested for Double Compression

Results

Results of Simulating Double Compression

Present Strange Results

Results of Testing Double Compression

Best to do by inspection

Conclusions

What worked what didn't

References

Shower Praise on Hany

Appendix 1

[Simulation_Script]


[Testing_Script] [Function_Style_Code]

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