In the field of image and signal processing we develop general algorithms as well as customer specific solutions adapted to real life problems in the fields of, e.g., microscopy imaging, surface quality control, and audio quality control. We provide a variety of methods ranging from data driven to classical signal processing techniques. We are specialised in combining classical image and signal processing methods for data pre-processing and feature extraction with machine learning methods for classification and evaluation tasks. The applied techniques comprise:
- Statistical and classical signal processing methods for denoising and pre-processing
- Multiscale approaches with applications to detection and recognition
- Computation of aggregated features for object characterization
- Pattern recognition and machine learning
Application fields are:
- Industrial image processing for surface and material inspection software, www.dynavis.org
- Biological image processing for microbiological image analysis software, www.gen-au.at
- Audio digitization and quality assessment tool