Tecnalia Computer Vision has image processing libraries that allow advanced enhancement, colour correction, noise removal, correction of lighting, out of focus correction and fog elimination. This system improves the quality of original images both for their visualization by operators as well as to enable computer vision algorithms.
Every day new biomedical devices are designed to obtain visual information with great relevance in the diagnosis, planification and surgery. These devices can show high quality representative images of the human body. However, this quality is limited by different factors. Among the latter are physical parameters of the acquisition system, such as the sensor’s resolution, its size, the frequency in the optical shutter, diffraction effects in the optical system, sensor sensitivity which make a lesser representation of the real image because of the system’s resolution and quality of the perceived image. In order to increase the resolution, the simplest solution in most situations is to substitute the acquisition device by another with enhanced features. However, this is not possible in certain applications as there is a need to miniaturize, to reduce costs, to limit radiation exposure or due to optical limitations (diffraction). Therefore, other techniques are necessary in order [...]
Doctors manually analyse each image provided by different systems (MRIs, TACs, X-rays). Advanced image processing algorithms can perform these tasks in an automated manner and can help the doctor in the diagnosis or screening processes. These algorithms integrate medical knowledge with anatomical and pathological image-based models. Advanced medical image analysis can assist in a faster and more precise diagnosis which in turn will reduce patient treatment costs. Tecnalia´s Computer Vision Group, in collaboration with the Image Diagnosis Service of Clínica IMQ Zorrotzaurre, has developed algorithms for image enhancement, for organ segmentation and for the characterisation of suspicious areas of the organs in hepatic pathology cases. These algorithms can be adapted for their use in the analysis of any other body organs. The introduction of image processing technologies in medicine is very useful and has great potential.
Our colleague Alberto Lago has been awarded the “Itsasargia 2016” (lighthouse in Basque language) by Vicinay Marine Innovation (VMi). This award recognizes the external partner that represents the VMi values, that person and guides them with their professional work and involvement. VMi is the R&D&i unit of the Vicinay Marine group and works on solutions for anchoring of floating infrastructures on the offshore industry providing advanced products, processes and services to their customers. Vicinay and Tecnalia hold a stable long term collaboration in different fields and technologies. Alberto is cooperating in projects that provide intelligence to the production process, cooperating on the data acquisition process with the aim of making Vicinay a reference for Industry 4.0. Alberto Lago is one member of the project development team and his unbeatable professionalism as well as his character and initiative have earned him this recognition. Congratulations Alberto! [...]
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!
Automated image analysis solutions for identification, cataloguing and monitoring of urban assets to enhance sustainability.
“Nature-based solutions” are actions inspired by nature which use the features and complex system processes of nature, such as its ability to store carbon and regulate water flows, in order to help societies address a variety of environmental, social and economic challenges in sustainable ways. Nature based solutions examples are green roofs, green walls, urban farms, etc. Knowing the capacity of a city to host these types of nature based solutions allows defining what adaptation actions are available in the municipality, which needs to be modified, new areas that could accommodate these solutions and finally identify what their potential for climate change adaptation with such solutions. Tecnalia Research & Innovation, with experience in the specific subject of climate adaptation, has developed a methodology to identify and map NBS in municipalities through the call KLIMATEK I + B + G: Projects R & D, Innovation and demonstration in climate change adaptation 2016. [...]
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.
Tecnalia actively collaborates with Erasmus Mundus Joint Master Degree CO·SI (Colour in Science and Industry). COSI / COlour in Science and Industry / is a two-year (120 ECTS) Erasmus+ Joint Master Degree, aiming to train the next generation of highly-skilled industrial experts in applied colour science, in various cutting-edge industries (photonics, optics, spectral imaging, multimedia technologies, computer graphics and vision) in a diverse range of sectors (including multimedia, health care, cosmetic, automotive, food-processing) bridging a talent gap in the industry where colour experts are in high demand. The 2 area of focus are spectral technologies and applied colour imaging. COSI is brought to you by a world leading university-business cooperation of 4 European universities (University Jean Monnet, University of Granada, University of Eastern Finland and Gjovik University College), 5 Asian universities and 15 industrial leaders across the globe. Call for Applications for 2016-2018 intake is now open! Apply [...]
The project ‘Robotics and flexible automation of food product packaging’ known as ‘PicknPack’ is a project of 4 years duration which holds a total budget of EUR 11,88Millon and an European Union contribution of 8,76Millon. It is coordinated by the University of Wageningen in the Netherlands and the consortium is made up of 14 partners from 9 different countries, including Tecnalia from the Division of Industry and Transport. PicknPack began on November, 2012 to provide the European food industry the benefits of flexible production, offering the advantage of reducing costs by increasing safety and hygiene in the packaging of its products by combining the unique ability to adapt to each product and lot size. In PicknPack 3 main modules that work in close cooperation are developed: a sensor module for evaluating the quality of the product, a robotic handling module guided by machine vision and an adaptive packaging [...]