Handling multiple materials for exposure of digital forgeries using 2-D lighting environments

Rieß, Christian; Unberath, Mathias; Naderi, Farzad; Pfaller, Sven; Stamminger, Marc; Angelopoulou, Elli

doi:10.1007/s11042-016-3655-0

Cited by 12 publications

(6 citation statements)

References 12 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Their method is generalized for complex lighting estimation and showed efficiency on a wide range of simulated, photographic, and plausible forgeries. Riess et al 8 detected fraud based on complex 2D lighting. The authors computed the lighting environment from multiple color surfaces using intrinsic contour estimation (ICE).…”

Section: Recent Workmentioning

confidence: 99%

“…Their method is generalized for complex lighting estimation and showed efficiency on a wide range of simulated, photographic, and plausible forgeries. Riess et al 8 . detected fraud based on complex 2D lighting.…”

Section: Recent Workmentioning

confidence: 99%

“…The advantage of physics-based techniques is that these techniques not only are limited to digital imagery but also can be used on analogy photographs. The disadvantage of such techniques is that these techniques require manual user interaction, making such methods unsuitable for batch processing 8 . This research paper aims to identify light source directions and reflectance parameters from a scene that is captured under multiple intensity light sources for laboratory-generated images.…”

Section: Introductionmentioning

confidence: 99%

“…The disadvantage of such techniques is that these techniques require manual user interaction, making such methods unsuitable for batch processing. 8 This research paper aims to identify light source directions and reflectance parameters from a scene that is captured under multiple intensity light sources for laboratorygenerated images. The technique is also tested for miscellaneous internet images of outdoor environments.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Digital image forgery detection under complex lighting using Phong reflection model

Rani

Jain

2022

J. Electron. Imag.

View full text Add to dashboard Cite

Image manipulation is transformed into a big issue for data integrity. The use of advanced imaging technology expends the regularity of multimedia forgeries. To detect such forgeries, some effective forgery identification methods are proposed to estimate the 3D lighting fingerprints by making certain suppositions related to the surface and reflection model. Incident lighting dispersal in a scene provides a physics-based key for exposing image exploitations. The proposed technique is more relaxed for multiple light source-based forgery detection. Also, the novelty of the technique is that it considers heterogeneous image surfaces, nearby surface geometry, and texture information to assess the lighting environment. The Phong reflection model is implemented to estimate the structural profiles. The method works in two phases. In the first phase, pre-processing over selected patches is performed followed by angle and error estimations in the second phase. To identify such forgeries, elevation angles ϑ concerning mounted light sources are estimated. The value of the elevation angle is computed for various patches of the image. The proposed method is relevant for a wide range of objects present in the image, i.e., not only limited to head positions, etc. To build up and validate the technique, comprehensive testing on the synthetic image dataset is done. Synthetic images are designed under different intensity light sources. Experimental results demonstrate a better forgery detection accuracy compared with other state-of-the-art methods in this domain. Also, the proposed technique is tested for generalized forged images. A comparative analysis with other related techniques is done to validate the proposed method using a synthetic image dataset. The results are pertinent to all type of images, and an error threshold is limited to 8 degrees with respect to the illuminant position.

show abstract

Section: Recent Workmentioning

confidence: 99%

Section: Recent Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Digital image forgery detection under complex lighting using Phong reflection model

Rani

Jain

2022

J. Electron. Imag.

View full text Add to dashboard Cite

show abstract

“…The splicing attack is one type of tampering in which different regions of the same or separate sources are combined to create a new fake image. In [21], Riess et al introduced a method for detecting image splicing through the change of illumination environment of the spliced object. They could overcome one of the biggest challenges which is computing the lighting environment from homogeneous materials.…”

Section: B Image Splicing Forgery Detectionmentioning

confidence: 99%

Robust Image Forgery Detection Using Point Feature Analysis

Youssef

Safwat

Salem

2019

Proceedings of the 2019 Federated Conference on Computer Science and Information Systems

View full text Add to dashboard Cite

Day for day it becomes easier to temper digital images. Thus, people are in need of various forgery image detection. In this paper, we present forgery image detection techniques for two of the most common image tampering techniques; copy-move and splicing. We use match points technique after feature extraction process using SIFT and SURF. For splicing detection, we extracted the edges of the integral images of Y , C b , and Cr image components. GLCM is applied for each edge integral image and the feature vector is formed. The feature vector is then fed to a SVM classifier. For the copy-move, the results show that SURF feature extraction can be more efficient than SIFT, where we achieved 80% accuracy of detecting tempered images. On the other hand, processing the image in Y C b Cr color model is found to give promising results in splicing image detection. We have achieved 99% true positive rate for detecting splicing images.

show abstract

Illumination Analysis in Physics-Based Image Forensics: A Joint Discussion of Illumination Direction and Color

Rieß

2017

Digital Communication. Towards a Smart and Secure Future Internet

View full text Add to dashboard Cite

Handling multiple materials for exposure of digital forgeries using 2-D lighting environments

Cited by 12 publications

References 12 publications

Digital image forgery detection under complex lighting using Phong reflection model

Digital image forgery detection under complex lighting using Phong reflection model

Robust Image Forgery Detection Using Point Feature Analysis

Illumination Analysis in Physics-Based Image Forensics: A Joint Discussion of Illumination Direction and Color

Contact Info

Product

Resources

About