Pattern Recognition and
Image Processing Group
Institute of Computer Graphics and Algorithms
PRIP Fakultät für Informatik, TU Wien Technische Universität Wien Fakultät für Informatik
2014-10-01: Important Notice
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Welcome to PRIP

PRIP group members

Modern sensors, like digital and video cameras, measure huge amounts of data day-by-day. Pattern Recognition and Image Processing aims at the extraction of information from such data.

Usually, the information to be extracted is related to pieces of data from the same environment that gives them meaning. Typical applications are tasks like autonomous navigation, the detection of anomalies in medical images or the prediction of an eruption of a volcano.

Simple tasks like the detection of human faces are already solved and solutions are commercially available in digital cameras. However, there is still a large number of complex tasks that require the system to incorporate knowledge to be efficiently used to enhance the recognition results and to give semantically appropriate interpretations. Such knowledge could be about the characteristics of the camera system, the composition and structure of the environment or the available processing strategies.

The large amount of data to be processed requires sophisticated representations that are both efficient and robust with respect to noise and distortions in the measurements.

Some problems may seem hopeless to solve at a first glance, but there are wonderful "natural" systems solving extremely hard tasks nearly effortlessly. We can learn by better understanding the human/biological perception mechanisms.


Are you looking for an interesting topic for your project, bachelor thesis or diploma/master's thesis?

In the following, you can find currently open topics, where we are actively searching for interested and motivated students.
For more information about the different options for projects and theses at PRIP click here.

Diplomarbeit/Praktikum aus Visual Computing
"Ermittlung der Klebstoffverteilung in Spanplattenquerschnitten"
Master's thesis/Practicum in Visual Computing
"2D tracking of Platynereis dumerilii worms during spawning"

Die Forscher am Kompetenzzentrum für Holzverbundwerkstoffe und Holzchemie arbeiten daran, die Menge und Verteilung des Klebstoffes in Spanplatten zu optimieren. Ihr Ziel ist es, die Menge an verwendetem Klebstoff möglichst weit zu reduzieren/optimieren ohne die Stabilität des Plattenwerkstoffs zu beeinflussen. Durch ihre Forschung sollen Ressourcen und Kosten eingespart werden.

Momentan werden die Mikroskopaufnahmen in einem aufwendigen Prozess manuell analysiert. Ziel dieser Diplomarbeit ist es diese Analyse weitgehend zu automatisieren.

Für mehr Informationen siehe Ausschreibungstext. holz icon

Kontakt bei Interesse: Walter G. Kropatsch, Nicole M. Artner


The marine annelid Platynereis dumerilii reproduces by external fertilisation and is semelparous, meaning that it spawns only once in its lifecycle. To maximise reproductive success these worms synchronise their spawning events with the lunar cycle and spawn primarily during new moon (Zantke et al., Cell Reports, 2013). In addition, P. dumerilii exhibit particular swimming behaviours during spawning, which are collectively described as a ‘nuptial dance’. The nuptial dance is initiated by excreted pheremones, stimulating male and female worms to swim in circles around one another and finally release sperm and eggs into the water.

The aim of thesis is to develop methods that enable 2D tracking of spawning worms from captured video and extract data to quantify specified behaviours.

For detailed information see announcement. worms icon

Contact: Walter G. Kropatsch, Nicole M. Artner

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