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Dr.-Ing. Christian Riess

Researcher in the Computer Vision (CV) group at the Pattern Recognition Lab of the Friedrich-Alexander-Universität Erlangen-Nürnberg

X-ray Phase Contrast, Image Forensics, Reflectance Analysis

My email address is listed here; or evaluate
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Image Processing for Phase-Contrast X-ray
  • Phase-contrast X-ray imaging is promising greatly improved sensitivity to varying types of soft tissue, that are challenging to distinguish with conventional X-ray. Our goal is to bring phase-contrast X-ray into clinical practice. Towards this, our group works on image processing of the phase-contrast images and 3-D reconstruction of tomographic acquisitions. My particular interest lies in the low-level, physics-based optimization of a grating-based setup for clinical tasks. Our Opens internal link in current windowresearch page lists all ongoing projects.

Image Forensics
The clothed tourist has been inserted.
The clothed tourist has been inserted.
Illumination is inconsistent on the tourist.
Illumination is inconsistent on the tourist.

We face an abundance of digital imagery, as well as the wide availability of photo editing software. Knowing that a digital image is authentic becomes increasingly important in many scenarios, for instance law enforcement, journalism and for insurance companies. In past times, human experts were called to assess images from dubious sources. Digital imagery opens novel opportunities, as well as new challenges in determining authenticity and origin. For instance, statistical artifacts, as well as physical properties like the lighting environment are very difficult to assess for humans. Computational methods can greatly support the expert in judging images under examination. Moreover, a number of methodologies can operate in a fully unsupervised manner, such that even large archives can be scanned for manipulated images.

A blind image forensics toolbox should consist of a number of diverse algorithms to detect tampered images. So far, manipulations can often be disguised against a particular detection algorithm, but with an increasing number of tools, it becomes less and less likely that a falsifier manages to evade all detection methods.

My main interest lies in the application of computer vision methodologies to image forensics. I am working on estimating properties of the illumination environment, and verifying the expected physical behavior of natural images.

Check out our project page for a full list of our work, as well as my publications on image forensics!

Color and Reflectance Analysis

The color of a pixel exhibits a mixture of illumination color, surface color and the in-camera processing. For white balancing, color-based recognition and image retrieval, a separation of illumination and surfaces is most important. Towards this goal, we investigate methods for the estimation of the illuminant color. Recent work includes the investigation of scenes with several different illuminants.

The Opens internal link in current windowproject page contains a list of works in this field. My publications on illumination estimation are listed Opens internal link in current windowhere.

Sensor data fusion for banknote processing

In a three-year project, we examined ways to optimize real-time banknote sorting using insights from sensor data fusion. Together with our industry partner Giesecke+Devrient, fusion principles have been examined for sensors based on diverse physical measurement principles. The project page is here.

RoboCup Small-Size Soccer
The "founding fathers" of the ER-Force team.
The "founding fathers" of the ER-Force team.

Our RoboCup group is a true student project: students design the hardware of small-size soccer-playing robots and develop the artificial intelligence. Meanwhile, our team "ER-Force" has a track record of successes. On the world championship in Singapore 2010, ER-Force advanced to the quarter finals!

Check out the project page, and the team's web page as well!