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Research
Media Security, Media Forensics & Watermarking
Description:
In the area of media security we are specializing in lightweight and partial encryption schemes for image and video data
with special emphasis on scalable media like JPEG2000 or H.264 SVC, and the assessment of the visual security such schemes do offer.
In media forensics, we have been working on the usage of PRNU-based sensor authentication techniques in a biometric centext, on the detection
of morphed portraits and deep fakes, and on robustness of copy-move forgery detectors.
In the watermarking area our focus is on
developing bitstream-based embedding techniques and key-dependency schemes for robust embedding techniques. Scalable watermarking and multiple watermarking are recent topics
of reasearch. In robust hashing, key-dependent wavelet transforms are also investigated as a means to provide security for such
schemes.
Funded Projects:
- Metrics for Assessing Visual Security of Image and Video Encryption Schemes (ViSecMetrics)
- Biometric Sensor Forensics (BioSensors)
- Computer Vision Enabled Multimedia Forensics and People Identification (IDENTITY), see the official CORDIS site.
- ICT COST Action IC1106: Integrating Biometrics and Forensics for the Digital Age
- ICT COST Action IC1206: De-identification for privacy protection in multimedia content
- Privacy-protected Video Surveillance on Scalable Bitstreams (PrivSurv)
- Structure-Preserving State-of-The-Art Video Watermarking (StructWM)
Biometrics
Description:
We focus on biometric modalities where image processing is conducted during feature extraction and
template generation (i.e. vascular biometrics like finger veins or hand veins, fingerprints, iris, face, retina, hand and foot geometry).
Current emphasis of our work
is on NIR sensor construction, sample data compression and encryption, as well as on privacy (like cancelable biometrics) and bias in biometric systems.
Questions of recognition robustness play an important in our research, and we also consider biometrics as applied e.g. in tree tracing and fish identification.
Funded Projects:
- Tools for the Generation of Synthetic Biometric Sample Data (GENSYNTH)
- Advanced Methods and Applications for Fingervein Recognition (FV2.0)
- Biometric fingerprints of trees: log tracing from forest to sawmill and early estimation of wood quality (TreeTrace)
- Biometric Capture Tool for Mobile Police Operations (BIOCAPTURE)
- Finger-based Biometrics for Austrian ATMs (AUTFingerATM)
- Pervasive and UseR Focused BiomeTrics BordEr ProjeCT (PROTECT), see the official CORDIS site
- Traceability of Logs by Means of Digital Images (TreeBio)
- Single-sensor Biometric Surveillance Combining Iris and Face (BioSurveillance)
Medical Image Analysis and Classification
Description:
Together with partners from different medical departments, we apply visual analysis and classification techniques to medical image data
targeted towards the development of computer-based decision support systems. Target imaging modalities so far have been gestro-intestinal endoscopic imagery
and (brain) MRI. On the one hand,
classical model-based texture classification features are developed and used, on the other hand data-driven learning based schemes are employed and customized to the
target imagery. We have been working on a staging technique for colon cancer, diagnosis of celiac disease, and discrimination of mild cognitive impairment from
epilepsy based on MRI.
Funded Projects:
- Research and Transfer lab on Artificial Intelligence in BioMedical Image Analysis (AIBIA)
- Towards Improved Celiac Disease Diagnosis (CeliacVideo)
- Physiological Markers for the Prognosis of Memory Decline (MemDecline)
- Endoscope Distortion Correction in (Texture Classification-based) Automated Diagnosis Support Systems (Undistort)
- Computer Assisted Mucosal Lesion Analysis in High Definition Digital Chromoendoscopic Colon Images Using Wavelet Techniques (ColonHD)
- Computer-assisted evaluation of endoscopic pictures of the duodenal mucosa of children with positive celiac serology (EndoCeliac)
- Computer-assisted Pit-Pattern Classification of Magnifying Endoscopic Colon Images Using Wavelet Techniques (FWFPIT)
- Computer-assisted Pit Pattern Analysis of Colonic Lesion (ENDOPIT)
Image- and Videocoding
Description:
We have been specializing in image and video compression techniques for over 25 years now.
In the development of techniques, emphasis has been given to adaptive techniques like wavelet packets or object based coding inspired by MPEG-4.
Also, cache efficient and parallel algorithms have been developed for a number of corresponding algorithms.
Often, we concentrate on scalable coding schemes like JPEG2000, MCTF scalable wavelet codecs, and H.264 SVC. More recently, we have been assessing the
employment of various lossy compression techniques in specific application contexts, like in biometric recognition, in media forensics and security, and in microscopy imaging.
Funded Projects:
General Computer Vision and Machine Learning Topics
Description:
Of course, we have also been involved in more general Computer Vision and Machine Learning topics, mostly collaborating either with companies, or supporting other research groups
not involved in visual data processing.
Funded Projects:
Multimedia Signal Processing and Security Lab |
Tuesday, 13-May-2025 04:59:58 CEST |