Thu. May 23rd, 2024
Face detection

Face detection or facial detection is a digital technology that refers to identifying human faces through digital means. It includes the use of smart computer scanning, particularly facial biometrics. Face detection is used in multiple industries pertinent to the sensitivity and security concerns. For example, in banks and financial institutions, detecting human faces through CCTV cameras and detecting human faces while opening up a bank account to recognize a customer is vitally important. 

However, there is a great deal of difference between the use of face detection in identity verification and other security surveillance. In this blog, we will identify and explain the use of Face Detection under the identity verification header and will explore it as a process. We will also discuss its use cases and what readers should know about an ideal face detection software.

Overview of Face Detection

As discussed earlier, face detection is a computer-driven technology used to identify human faces through digital images. Experts in the field of identity verification define face detection as an Artificial Intelligence (AI)-driven technology that is capable of identifying and recognizing human faces anywhere.

Uses of Face Detection

Face detection has become one of the ideal ways of improving security and other operations of businesses. Primarily, in state security, law enforcement and intelligence agencies use face detection to identify and catch criminals well before they act. They do it through hardcore surveillance via CCTV cameras, smartphone cameras, and other video recording devices. Here are some important use cases of ace detection in different sectors:

  1. Identity Verification

In KYC (Know Your Customer) customer onboarding has become easy and seamless after the introduction of remote KYC through smartphones. Now banks, FIs, and other MSBs (Money Service Businesses) can easily onboard their customers and conduct their Identity Verification within seconds via selfie cameras. This process is based on Face Detection through a selfie camera that detects a customer’s face, matches it with the identity information present in the database and identity documents, and then verifies a customer’s identity to allow him the use of services safely and securely. This is done to protect genuine customers from fraud, money laundering, and other financial crimes.

  1. Marketing

Another important use of face detection is that customer databases are collected through face detection from stores, malls, and shopping malls. Whenever customers enter a building, the CCTV cameras record their faces in which attributes like, gender, age, race & color are recorded. This data is then used to analyze the customer preferences and then a marketing campaign or ad is targeted onto the customers according to the data extracted through face detection.

How does Face Detection work?

Face detection application software works on the principle of identifying the facial features of human faces. Most importantly it recognizes the difference between a human face and an artificial face. The latest facial biometrics systems are sophisticated enough to accurately detect a living human face according to the following approach:

  • Facial Detection uses AI algorithms to detect human faces from a digital face image.
  • It searches for human facial features among which eyes are the first ones to be detected. Then it searches for the nose, lips, and other essential features. 
  • Once the facial features and the face shape are correctly detected, the algorithm confirms that it is a human face.
  • The facial detection algorithms are also trained through AI on a massive database of almost all possible matches through which it can accurately detect a human face in a digital image or a photograph too.

What happens after Face Detection?

Face detection is the first step but certainly not the final one in facial recognition. After a human face is detected, the identity verification procedure continues to search for possible matches from a certified database. Once a match from a real identity is found the facial identity of the image or a person is verified and authenticated.

Challenges in Face Detection

Face detection can be challenging in different scenarios due to certain limitations and concerns that identity verification vendors should know about. The users whose faces are being detected should also know that their consent and privacy are vitally important to protect their dignity and to protect their facial data from being misused. 

  1. Cost 

The cost of implementing a face detection system can be a burden. If a retailer requires face detection to minimize shoplifting cases, he/she may want to consider a low-cost face detection just like the one in his/her smartphone camera. But this will only help in the detection of human faces and recording videos. It may not be able to identify a shoplifter before time due to constraints. 

  1. Identity Theft

A major risk and challenge in identification through facial recognition is identity theft and spoofing attacks especially the ones using AI-based deepfake attacks. Deepfakes are one of the most sophisticated and highly realistic human facial identities created by using generative AI. Face detection being limited to only detecting faces cannot differentiate between a deepfake and a real human face on its own. It requires the use of AI-based anti-fraud mechanisms to do the job.

  1. Morphing

Morphing is another type of digital image manipulation technique that can create or change an entire human face digitally. The morphed images are then used for bypassing facial recognition and penetrating a system or illicit gains.

How Face Detection can be Enhanced for Improved Facial Recognition?

Facial detection itself is limited to only detecting human faces and it requires technological amalgamation with other important systems like digital KYC identity verification and AML Screening systems. After a face is detected, KYC IDV and AML Screening will decide whether to allow the presented image and face or to reject it.  

Final Word

Facial identity verification is important in current times. It provides robust security measures against threat vectors like deepfakes, morphing, and other forms of identity theft. Face detection should be enhanced by leveraging AI, machine learning, and cloud computing to accurately and swiftly detect and recognize human faces. For this purpose the use of an ideal identity verification system is critical. 

Facia is the world’s fastest facial recognition solution that swiftly identifies and verifies human faces for the sole purpose of protecting digital identities. Due to its diverse features including interoperability and integration with multiple OS and devices, Facia is the best choice for  businesses requiring robust customer identification measures.

By RSTech Zone

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