How to create a face recognition app for your business
The biometrics technology is widely used when building applications. It includes face recognition, voice recognition, hand geometry, signature recognition referring to evaluating and identifying the unique physiological, behavioral person characteristics. They can be used for identification and verification.
The global biometric market is expected to reach 1,820 million U.S. dollars by 2024, growing at a CAGR of 9.7% from 2016 to 2024. Face recognition technology has a fair share of the market and is expected to carter fertile ground in the following years. A fingerprint identification feature is already used on our mobile devices, consequently, the facial recognition tends to be widely applied as well.
In this article, we have collected some reasons why face recognition app is worth implementing and offered you a brief review of the main algorithms used when building a face recognition mobile app.
The benefits the face recognition technology offers
It has unmatched advantages to be applied in various business areas. Below you can read the essential ones:
- Preventing identity fraud due to markedly more difficulties to forge biometric data, such as voice/facial feature.
- Improving public security by fast identifying the suspected people.
- Saving companies and customers time and money by eliminating paperwork associated with identification.
- Improving customer experience with biometrics that helps authenticate users and prevent fraud, and also speeds up conversational commerce, providing customers with a more engaging experience.
How the facial recognition technology works
Facial recognition is the enhanced application of image analysis technology. The overall process of face recognition takes the following stages.
1.Detection.
2.Extraction.
3.Matching.
4.Recognition.
Firstly, the program detects the face in the image. Secondly, it extracts the required data from the image that involves obtaining relevant facial characteristics (eyes spacing, variations, angles, and ratios). Thirdly, the program compares extracted pattern with the ones stored in the database. Finally, the program recognizes the face and matches it to a name stored in the database and then decides whether the pattern matches or not.
