computer vision & biometrics

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Contribute to more accurate healthcare diagnoses, secure identification, and sustainable agriculture practices through advanced computer vision systems.

Enabling computers to understand images and patterns through the analysis of biometric data like fingerprints, facial scans, or voiceprints can lead to innovative solutions for many real-world challenges. For instance, you can help law enforcement identify suspects through facial recognition. Or you can make financial transactions more secure by using sensors to visualise vein patterns in a finger. You will learn to solve key challenges when it comes to dealing with biometric data. For example, in what ways can you adequately secure biometric data so that it isn’t compromised? How can you design inclusive and unbiased electronic systems that work equally well for all individuals despite their skin tone, gender, or physical disabilities? This is the impact you can have if you choose the specialisation in Computer Vision & Biometrics.

“With the new EU regulations, you have to make sure that a biometric system can explain the results it provides. For example, when it identifies a person as a match at a specific moment, it must be able to explain how it arrived at that conclusion. How can you create a trustworthy, transparent system that can explain how and why it has made certain decisions?”

Dr. Luuk Spreeuwers, Programme mentor Computer Vision & Biometrics

What is Computer Vision & Biometrics?

The focus of this specialisation is on the system level, and you will learn advanced techniques to analyse biometric data, develop sensors, and process signals. For example, sensors capture fingerprints, facial scans, or voice patterns. How can you design them in such a way that you ensure the accurate collection of biometric data? Another important part is computer vision. What are the most suitable techniques to extract meaningful information from an image or to detect image manipulations, such as deepfakes? In addition, you can focus on pattern recognition and machine learning and explore techniques to identify and categorise patterns within the data.

Examples of courses you will follow within this specialisation:
  • Learn methods such as object, place, and face recognition to automatically analyse and extract information from images or videos in the course Advanced Computer Vision and Pattern Recognition.
  • What are the various modalities of biometric recognition and how reliable are they? Learn about face, iris, fingerprint, and finger vein recognition in the course Introduction to Biometrics.
  • Assess the performance and effectiveness of biometric systems with limited amounts of data in the course Advanced Topics in Biometrics.

Thanks to our collaboration with the government and the police, and our involvement in EU projects, you will be able to work on exciting real-life cases. For example, you can develop face recognition systems that are less vulnerable to image manipulations like face morphing or deep fakes. Or you can work on explainable and unbiased biometric recognition. For example, we work with the Netherlands Forensic Institute (NFI) on developing face recognition methods that provide a decision or similarity and also explain the basis for these outcomes, such as using the shape of the eyebrows and the presence of facial marks. Another important field of research is bias in various methods, ensuring that recognition results are fair and systems do not favor certain groups over others.

What will you learn?

As a graduate of the Master's in Electrical Engineering with a specialisation in Computer Vision & Biometrics, you have acquired specific scientific knowledge, skills, and values that will help you in your future career.

  • Knowledge

    After completing this Master’s specialisation, you:

    • have a solid knowledge of traditional computer vision techniques and deep learning methods;
    • have an understanding of biometric systems, various modalities, sensors, recognition, and evaluation metrics;
    • have an in-depth knowledge of machine learning, pattern recognition, deep learning, neural networks, and AI.
  • Skills

    After successfully finishing this Master’s specialisation, you:

    • can critically assess academic literature on computer vision and biometrics;
    • can design, implement, and evaluate (parts of) biometric and computer vision systems;
    • can independently design and carry out experiments in the domain of computer vision and biometrics.
  • Values

    After completing this Master’s specialisation, you:

    • recognise the importance of responsible data use, privacy protection, and fair treatment of individuals’ data;
    • strive to create systems that work well for diverse people in all circumstances;
    • understand the need for explainability of the results of computer vision or biometric systems.

Other master's

Is this specialisation not exactly what you are looking for? Maybe one of the other specialisations suits you better. You can also find out more about related master’s at the University of Twente:

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