Journal ArticleDOI
Digital Single Lens Reflex Camera Identification From Traces of Sensor Dust
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TLDR
Experimental results show that the proposed detection scheme can be used in identification of the source digital single lens reflex camera at low false positive rates, even under heavy compression and downsampling.Abstract:
Digital single lens reflex cameras suffer from a well-known sensor dust problem due to interchangeable lenses that they deploy. The dust particles that settle in front of the imaging sensor create a persistent pattern in all captured images. In this paper, we propose a novel source camera identification method based on detection and matching of these dust-spot characteristics. Dust spots in the image are detected based on a (Gaussian) intensity loss model and shape properties. To prevent false detections, lens parameter-dependent characteristics of dust spots are also taken into consideration. Experimental results show that the proposed detection scheme can be used in identification of the source digital single lens reflex camera at low false positive rates, even under heavy compression and downsampling.read more
Citations
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Journal ArticleDOI
An Overview on Image Forensics
TL;DR: The aim of this survey is to provide a comprehensive overview of the state of the art in the area of image forensics by classifying the tools according to the position in the history of the digital image in which the relative footprint is left: acquisition- based methods, coding-based methods, and editing-based schemes.
Journal ArticleDOI
Digital image forgery detection using passive techniques: A survey
TL;DR: An attempt is made to survey the recent developments in the field of digital image forgery detection and a complete bibliography is presented on blind methods for forgery Detection.
Journal ArticleDOI
Vision of the unseen: Current trends and challenges in digital image and video forensics
TL;DR: The emerging field of digital image forensics is introduced, including the main topic areas of source camera identification, forgery detection, and steganalysis, including a critical analysis of the state of the art, and recommendations for the direction of future research.
Journal ArticleDOI
A bibliography on blind methods for identifying image forgery
Babak Mahdian,Stanislav Saic +1 more
TL;DR: An extensive list of blind methods for detecting image forgery is presented and an attempt has been made to make this paper complete by listing most of the existing references and by providing a detailed classification group.
Journal ArticleDOI
First Steps Toward Camera Model Identification with Convolutional Neural Networks
TL;DR: Zhang et al. as discussed by the authors proposed a data-driven algorithm based on convolutional neural networks, which learns features characterizing each camera model directly from the acquired pictures, and showed that the proposed method outperforms up-to-date state-of-the-art algorithms on classification of 64 × 64 color image patches.
References
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Fast Normalized Cross-Correlation
TL;DR: This short paper shows that unnormalized cross correlation can be efficiently normalized using precomputing integrals of the image and image over the search window.
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
The trustworthy digital camera: restoring credibility to the photographic image
TL;DR: The digital signature standard (DSS) as mentioned in this paper was proposed to authenticate electronic mail messages by using modern cryptographic techniques to prevent the explosion of very capable personal computers from driving up the incidence of doctored photographs being passed off as truth.
Proceedings ArticleDOI
Blind source camera identification
TL;DR: A number of features are proposed which could be used by a classifier to identify the source camera of an image in a blind manner and shown reasonable accuracy in distinguishing images from the two and five different camera models using the proposed features.
Journal ArticleDOI
Nonintrusive component forensics of visual sensors using output images
TL;DR: This paper introduces nonintrusive component forensics as a new methodology for the forensic analysis of visual sensing information, aiming to identify the algorithms and parameters employed inside various processing modules of a digital device by only using the device output data without breaking the device apart.