VARPA is the acronym of Visión Artificial y Reconocimiento de Patrones (Computer Vision and Pattern Recognition; Digital Image Processing), a research group inside the Department of Computer Science of the University of A Coruña (UDC), Spain. The members of VARPA develop their teaching and research activities on Digital Image Processing and computer vision research, development and applications.
The specific research lines at VARPA are:
- Retinal Image Analysis: One of the most active fields of work in the VARPA Group is the ophtalmology, in particular the analysis of eye fundus images (retinal images). The retinal image processing is a very interesting and demanding field, having a lot of practical applications, such as the development of applications for massive medical revision and the research in pharmacology effectiveness. Currently, we are focused on the following topics:
- Drusen detection
- Red lession detection
- Automatic computaton of the Arteriolar-to-Venular Ratio
- Biometrics: Retinal vessel tree is a suitable biometric pattern as it's unique for each individual, it's very hard to forge and, unless some pathologies arise, it doesn't change in time. VARPA group has developed an authentication system based on this retinal vessel tree and we are currently working on the individual characterization based on the feature extraction from the vessel tree. This will allow to build an easily and more robust biometric pattern.
- Perceptual organization: Perceptual grouping refers to the human visual ability to extract significant image relations from lower-level primitive image features without any knowledge of the image content and group them to obtain meaningful higher-level structure. Our experience in perceptual organization consists in the design and implementation of a fully automatic framework for the detection of structured objects in 2D images.
- Deformable Models: We have developed methodologies for both 2D and 3D segmentation and reconstruction based on deformable models. We have developed procedures to overcome some of the limitations of the classical deformable models. Also, we have apply evolutionary techniques to the deformation process.
The group promotes industrial development of computer vision applications and collaboration with research in the same field. VARPA fundamental goals are innovation and industrial competitiveness promotion based on computer vision research and development, and collaboration with industry in technological projects development.
Principal Researcher: Manuel Francisco González Penedo