Glossary Face Recognition

Face Recognition

Face Recognition: Applications and opportunities

Face recognition technology is now used in many areas of everyday life, from unlocking smartphones to accessing personal bank details. In the digital era, security and identity verification are becoming increasingly important. Therefore, it is essential to develop new solutions for these areas.

Face recognition is an innovative biometric identification technology that allows people to be identified and verified based on their unique facial features. Companies and organisations are increasingly using it to control access to sensitive areas, enhance security, and improve customer experience.

What face recognition means

Face recognition is an advanced biometric identification technique that uses specific facial features to identify individuals. Every face has a unique combination of these features, such as the shape of the eyes, nose, lips and jaw. These features are captured and stored as a 'faceprint' or 'biometric template'.

How does face recognition work?

Face recognition is based on complex algorithms and technologies, particularly artificial intelligence. Technically sophisticated systems can identify people even if their appearance has changed — for instance, if they have a different hairstyle, are wearing glasses, or have simply grown older. When used alongside processes such as two-factor authentication, system security can be enhanced even further.

The most common algorithm is the Convolutional Neural Network (CNN). This algorithm is based on the principle of a neural network, whose structure and mode of operation enable it to recognise complex patterns and features.

When using CNN to recognise faces, the network is first trained using a large number of images of familiar faces. It then analyses these images, learning the unique features, patterns and structures that characterise each face. These features include the position and shape of the eyes, nose and lips, as well as the context of the face.

Once trained, the CNN can be used to identify or verify faces. The face to be identified is divided into smaller sections, which are then sent through the network for analysis. The CNN then analyses the characteristics of each section and compares them with the stored templates in the database. Based on the features and patterns it has learnt, the CNN can calculate the probability that the face being viewed matches a particular person.

The advantage of CNN-based facial recognition technologies is that they are highly precise and effective, even with large databases and in real time. They can also account for changes in appearance while still delivering reliable results.

Face recognition systems are constantly evolving, and there are other algorithms and approaches available. However, CNN is currently the most widely used and successful method. Face recognition generally involves several steps to identify and verify faces.

Step-by-step to digital face recognition

Step 1 - Face recognition with hair cascade classifier: The algorithm recognises typical facial features such as eyes, nose and mouth and aligns the face for the next steps.

Step 2 - Analysis by CNN: The Convolutional Neural Network extracts characteristic features and learns to precisely identify faces using large image data sets - a common method in modern authentication procedures.

Step 3 - Comparison with database: The extracted features are compared with stored templates. The Euclidean distance measures the similarity - the smaller the distance, the higher the match.

Face recognition: advantages and disadvantages

Face recognition at PXL Vision: precision meets data protection

At PXL Vision, we use face recognition technology as an integral part of our secure identity verification process. Our solutions are based on AI applications, including classic computer vision and machine learning. By training with large data sets, we can achieve highly accurate results in under 30 seconds.

Our systems are GDPR- and DSG-compliant and do not require large cloud providers. Data from Switzerland does not leave the country. In addition, modern technologies prevent personal data from being traced.

Modern identity verification with biometric face recognition

Face recognition technology is constantly evolving, as are the possibilities for secure digital identification. PXL Vision combines cutting-edge technology with the highest data protection standards, offering companies a reliable identity verification solution for the future. Get in touch – we'd be happy to advise you on a solution.