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Using anisotropic diffusion for efficient extraction of sensor noise in camera identification.

Wiger van Houten¹, Zeno Geradts

¹Digital Technology and Biometrics Department, Netherlands Forensic Institute, The Hague, The Netherlands. wawvanhouten@gmail.com

Journal of Forensic Sciences

|February 15, 2012

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Researchers developed a simple, fast algorithm to extract digital camera fingerprints from images. This method outperforms complex wavelet filters, enabling quicker and easier device origin identification.

Area of Science:

Digital image forensics
Computational imaging

Background:

Digital cameras possess unique, intrinsic fingerprints for device identification.
Current methods for extracting these fingerprints often involve complex filters.

Purpose of the Study:

To introduce a simpler, faster algorithm for extracting digital camera sensor noise.
To compare the proposed algorithm's performance against existing wavelet and median filters.
To evaluate the effectiveness of a fingerprint enhancement technique.

Main Methods:

A straightforward algorithm was employed to extract sensor noise from digital images.
The proposed method was tested on approximately 7500 images from 69 distinct cameras.
Performance was benchmarked against a common wavelet filter and a simple median filter.

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Main Results:

The proposed simple algorithm demonstrated superior performance compared to the conventional wavelet filter.
The new method significantly reduced the time required for fingerprint extraction.
The algorithm proved to be easily implementable and parallelizable.

Conclusions:

A simple sensor noise extraction algorithm offers a more efficient and effective approach to digital camera fingerprinting.
This technique provides a viable alternative to more complex methods for device origin determination.
The findings suggest potential for faster and more accessible image forensics.