Our colleague at Tecnalia Computer Vision, Arantza Bereciartua has successfully presented her PhD dissertation at the Control Engineering and Automatics Department of the University of the Basque Country. This work has been co-tutored among this University and Tecnalia. The work presents a 3D variational segmentation method for liver segmentation over multisequence mRI images. This work has also been presented in [Computer Methods and Programs in Biomedicine] and in [Biomedical Signal Processing and Control] journals. Congratulations!
Convolutional neural networks make Tecnalia’s SURFIN Hot surface inspection® system evolve to assure automatic quality control
Tecnalia has presented the new version of its SURFIN Hot surface inspection® system at the First European Machine Vision Forum of the European Machine Vision Association (EMVA). SURFIN performs in-line real-time detection and classification of surface defects (e.g. roll marks, cracks, etc.) from the manufacturing process of metallic products such as bars, tubes, billets, slabs, beam blanks or structural profiles. The systems are installed in the production line. It can detect defects at the early stages in the production process, when the product is still incandescent (>1000ºC). This allows preventing the unnecessary addition of value to it and having traceability of all the production, allowing a preemptive maintenance due to the information it obtains. The system is based on special 2D imaging with laser or LED-based imaging, and makes use of machine learning techniques. SURFIN has been upgraded by replacing the previous detection and classification module –supported by opaque handcrafted [...]
Our colleague at Tecnalia Computer Vision, Adrián Galdrán has successfully presented his PhD dissertation at the Applied Mathematics Department of the University of the Basque Country. This work has been co-tutored among this University and Tecnalia. The work, entitled “Visibility Recovery on Images Acquired in Attenuating Media. Application to Underwater, Fog, and Mammographic Imaging”, presents novel variational algorithms to restore the information contained on degraded images acquired under attenuating conditions such as, underwater, haze or human tissue. This restoration plays an essential role for the performance of ulterior image analysis and understanding algorithms. The developed algorithms have been already applied to natural, underwater, medical and steel process images both for restoration purposes and to improve the performance of analysis algorithms. Congratulations!
The Computer Vision group has been awarded with the International Excellence Group (GEI) recognition by Tecnalia. At Tecnalia, GEI recognition is given to highly specialized teams that outstand both on academic research (PhD Thesis, patents exploited by 3rd parties, relevant research papers…) and on market oriented approach (International R&D contracts, development of technological assets… ). The existence of these groups at Tecnalia potentiates focused applied research with greater outcomes to industry. Tecnalia evaluation committee highlighted the international contracts with different transnational companies of our group and the international awards received by the team. We would like to thank our collaborators and companies that along these years have trusted in the group.