Project Supervisor: Prof. Dr.-Ing. R.-R. Grigat
Coworker: Dr.-Ing. Yaroslav Gevorkov
Running time:04.2016 - 04.2020
Financing:  Deutsche Elektronen-Synchrotron DESY
Publications: here

References: Real-time capable algorithms,  Real-time data processing,  GPU computing (CUDA),  Pattern recognition, Crystallography, Femtosecond X-ray imaging

In many scientific and industrial applications, the structure of molecules is of high interest.
As an example, in pharmacy one is interested in the structure of viruses or amino acids.
To identify the structure, it is not possible to construct microscopes that use visible light, since the resolution is limited by the wavelength of the light.
The solution is to use light sources with higher energy, such as an X-ray source. We use X-ray diffraction to extract information abut molecules out of artificially grown micro crystals. The X-ray sources typically are X-ray Free Electron Lasers (XFELs) that can deliver a very high radiation dose, far in excess of what the crystal could normally tolerate, in a time span in the range of femtoseconds.
The crystal diffracts the X-rays before it is destructed, overcoming the effect of radiation damage [1]. Due to the limited availability of beam time, the optimization of the collection process is crucial for obtaining good results.
Therefore, the real-time analysis and monitoring of the collected data is of great interest. We develop algorithms and tools that are capable of meeting real-time constraints of current X-ray sources while retaining or improving the results compared to the conventional methods of choice.

[1] Chapman et al. J. "Femtosecond diffractive imaging with a soft-X-ray free-electron laser". Nature Physics 2006, 2 (12), 839-8

Project Supervisor: Prof. Dr.-Ing. R.-R. Grigat
Coworker: M.Sc. Luh Putu Ayu Prapitasari
Running time: 10.2012 - 09.2016
Financing: Sholarship from Indonesia
Publications: here
References: Kruppa's equation, absolute conic, calibration

The demands in camera self-calibration is very high but unfortunately, at the moment, there is no mature method has been found or developed so far.

In this research we aim to develop a robust camera self-calibration algorithm for general cameras, either using single or multiple view as the input. The camera model is restricted to be a pinhole camera which is supposed to be projective camera, including the smartphone cameras. As the first method in self-calibration was the Kruppa's equations which is worked based on the absolute conic, then the method that we are going to develop will first investigate the Kruppa's as the basic and for the better understanding of the problem.

The possibility of the algorithm to be used for stereo camera will also be investigated for the future use.

Project Supervisor: Prof. Dr.-Ing. R.-R. Grigat
Coworker: Dr. Dipl.-Ing. Frank Herold
Running time: 10.2000 - 9.2004
Financing: Industry
Publications: here
References:

Particularly in the automobile industry the quality assurance is accomplished by safety-relevant cast parts by a X-ray. This non destructive testing method supplies digital graphic data by so-called image amplifiers or with new flat detectors. Today's algorithms for the detection of casting defects (e.g. pipe, Poroesitaeten) need up to 6 months a lasting training phase by highly-qualified technical personnel (engineer). A goal of this project is to automate the training procedure with simultaneous speed increase. Here the graphic control surface of the training algorithm on a PC system is to be so user friendly that an intuitive
operability also non--engineers becomes possible. To automatic casting defect detection a nonlinear, non-local filter procedure for the employment comes. This procedure ben÷tigt a training phase, before it is then used to the radiograph segmenting. It is called Trained median filter (TMF)

Radiograph segmenting of a knuckle

Project Supervisor: Prof. Dr.-Ing. R.-R. Grigat
Coworker: Dr. Shuyan Zhao
Running time: 10.2001 - 11.2006
Financing: TUTech
Publications: here
References: MPEG-7, Content Based Access , Databases

The increasing availability of multimedia (still images, video and audio) ensures the need for the techniques of content based access to multimedia data. Conventional keywords search is not sufficient because of its ambiguityof description of query

targets and incapability of representation of the multimedia content. In this project we aim at investigating the approaches for content based access to image databases and developing a face image retrieval system that can search a certain type of faces, for example, a faceof a young European woman. The research includes: description of content, interpretation of features, similarity measures, interaction, and so on.

Project Supervisor: Prof. Dr.-Ing. R.-R. Grigat
Coworker: Dr. Islam Shdaifat,  Dr. Dipl.-Ing. Ralph Kricke
Running time: 01.2001 - 10.2007
Financing: Industry
Publications: I. Shdaifat,   R. Kricke
References: Automated speech perception, lip and face recognation

Automated speech perception systems are sensitive to background noise. They fail totally when multiple speakers are talking simultaneously which is known as cocktail party effect. It is desirable to reach the human ability of speech recognition especially the ability of the speech reading.

The potential for joint audio-visual-based speech recognition is well established on the basis of psycho-physical experiments. The project focuses on the extraction of relevant visual speech features from the lips and mouth area and examines the suitability of these features for improving the speech recognition.

Project Supervisor: Prof. Dr.-Ing. R.-R. Grigat
Coworker:Dipl.-Ing. Thorsten Gernoth
Running time: 01.2007 - 10.2010
Financing: TUTech
Publications: here
References: Content Based Access , Databases

Nowadays there is a high demand for security on the airplanes. In this project, we aim at developing an integrated security system using pattern recognition methods. Signals from audio, video, and seating sensors will be jointly employed to achieve robustness.

Current face recognition systems can achieve satisfactory performance only in controlled situations. Generally recognition performance drops when confronted with varying lighting conditions, changed head poses or natural changes of the faces, for example due to condition or behavior of the persons who should be recognized. In this project, a special focus is therefore placed on analyzing the influence of these factors on features which are used for face recognition. We aim at investigating approaches for face recognition which are robust enough to meet the requirements of an access control system for a cockpit.