The aim of this research is to study image features and processing methods for detection of visual code regions (1D barcode, 2D datamatrix, OCR characters), with special focus on highly accurate and efficient algorithms that can be adapted for real industrial applications.

We consider the problem of estimation the parameters of transformations aligning two binary images. The advantage of our algorithm is that it is easy to implement, less sensitive to the strength of the deformation, and robust against segmentation errors.

SZOTE-PACS is the Picture Archiving and Communication System of Albert Szent-Gyorgyi Medical University. It is able to collect studies from CT, MR, SPECT, US and modalities and convert them into DICOM format.

A joint project is in process between the University of Szeged Image Processing Group and Department of Optics and Quantum Electronics and GE Medical Systems (GEMS) Budapest, to study the problems connected with CT image corrections.

Helicopter rotor blades were tested by combined neutron and X-ray radiography. Due to the large size of the rotor blades, several images had to be taken and put together to compose one big image. We developed an interactive solution based on artificial markers.

The main contribution of this project is the implementation of a Markovian image segmentation model on a new chip, called CNN (Cellular Neural Networks), which is capable to do the task in real time.