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Proceedings ArticleDOI

Source camera identification using SPN with PRNU estimation and enhancement

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TLDR
This work analyzes the PRNU estimation and enhances the content of the PRnU for better accurate identification of the source camera in sensor pattern noise associated with digital images.
Abstract
The sensor pattern noise is associated with digital images, due to imperfection in the chip of image sensor manufacturing process and it causes pixel sensitivity variation in the imaging sensor. The distinct property of these pattern noises makes it unique to that image sensor. Therefore, it acts as ‘fingerprint’ of that particular imaging sensor. The main contributor of sensor pattern noise is Photo Response Non-Uniformity noise (PRNU). In this proposed work, we analyse the PRNU estimation and enhance the content of the PRNU for better accurate identification of the source camera. The PRNU extraction consists of three stages: filtering, estimation and enhancement stage. Each stage consists of various techniques incorporated for the PRNU extraction. The experiments were conducted on natural images taken from the different camera models. For our experiment, 300 images from 6 different camera models are used and identification of source camera of a given image is done by correlating the PRNU reference pattern with the noise residual model obtained from the test image.

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Citations
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References
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Journal ArticleDOI

Digital camera identification from sensor pattern noise

TL;DR: A new method is proposed for the problem of digital camera identification from its images based on the sensor's pattern noise, which serves as a unique identification fingerprint for each camera under investigation by averaging the noise obtained from multiple images using a denoising filter.
Journal ArticleDOI

Exposing digital forgeries in color filter array interpolated images

TL;DR: This work quantifies the specific correlations introduced by CFA interpolation, and describes how these correlations can be automatically detected in any portion of an image and shows the efficacy of this approach in revealing traces of digital tampering in lossless and lossy compressed color images interpolated with several different CFA algorithms.
Proceedings ArticleDOI

The 'Dresden Image Database' for benchmarking digital image forensics

TL;DR: A novel image database specifically built for the purpose of development and bench-marking of camera-based digital forensic techniques and is intended to become a useful resource for researchers and forensic investigators.
Journal ArticleDOI

Source Camera Identification Using Enhanced Sensor Pattern Noise

TL;DR: This work proposes a novel approach for attenuating the influence of details from scenes on SPNs so as to improve the device identification rate of the identifier.
Journal ArticleDOI

The Dresden Image Database for Benchmarking Digital Image Forensics

TL;DR: A novel image database specifically built for the purpose of development and benchmarking of camera-based digital forensic techniques and is intended to become a useful resource for researchers and forensic investigators.
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