Biometric security technologies are increasingly becoming more sophisticated due to the rising cases of data breaches. One of the laudable security technology introductions in recent years is facial recognition software. This set of software is designed to use artificial intelligence and machine learning to scan human faces and match them against existing biometric data to confirm if an individual should be granted access to an application, computer system or environment.
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With the rise in the adoption of facial recognition software across organizations, we look at the top facial recognition software vendors and various use cases of the technology in recent years.
Facial recognition software vendors
Amazon Rekognition is a popular provider of facial recognition services around the world. The Rekognition software has facial search and facial analysis features that help record facial detection, user verification and public security use. In addition, the software has a huge database at its disposal, enhancing its accuracy in object recognition.
With the Amazon Rekognition software, image and video hosting providers can easily apply content moderation capabilities to their applications and websites. Content moderation helps to identify inappropriate or unsafe images or videos. Furthermore, this software can label a wide range of objects and detect custom logos, celebrities and texts.
You can get started with this software by using their 12 month free tier. This allows you to analyze up to 5,000 images/month for 12 months. Within these 12 months, you can store up to 1,000 face metadata objects. After 12 months, users are charged based on the pay-as-you-use pricing model.
BioID is another top provider of facial recognition solutions. Their FRS is cloud-based and can be accessed from anywhere using APIs. BioID has two major features: Liveness detection and photoverify facial recognition.
BioID’s liveness detection feature is a wonderful tool for fighting online frauds. With it, you can easily detect live persons, spoofing attacks and differentiate humans from avatars. However, this feature requires some level of human interaction to function.
The photoverify feature is a solution for your KYC verification, facial log-in use cases and other facial recognition needs. For pricing, you can contact BioID support.
Paravision is a cloud-based AI recognition solution with several quality characteristics.
Founded to solve activity recognition and facial recognition issues, Paravision relies on real-time streaming and frame-based techniques to provide face detection solutions. With this software, you can easily detect and verify faces and map their locations during live sessions. Some other features that can serve your needs are face clustering, face comparison, spoof detection, phenotype detection and age estimation.
Paravision use cases include access control systems, KYC verification and border security control. You can check out this software by requesting their demo.
Cognitec’s live video scan feature enables your system to detect faces in live video streams. It takes things a step further by numbering the facial detections and recording the demographics. This particular solution also has the enterprise version designed for huge business enterprises.
There is also an ID biometric verification solution for businesses and law enforcement agents. Cognitec use cases include physical security, law enforcement and ID management. You can contact their sales team for details on how to purchase this product.
Luxand is an FRS company that offers a variety of high-end facial recognition solutions. Although a great tool in the hands of commercial users, Luxand is most suitable for AI developers who are looking for a solution to rely on for facial detection and recognition within their Java, .NET, C++ and Delphi apps.
Other industries that may find the Luxand technology useful are the entertainment sector, banks, biometric identity and security firms. Their technologies are used by commercial organizations to automate the process of uploading facial images to databases.
Kairos is another formidable facial recognition solution provider that allows users to host the software on their servers or integrate it using APIs. This FRS solution covers a lot of facial recognition needs, such as spoof detection, multi-face detection, age detection and gender detection.
Additionally, you can leverage the software’s facial coordinates and diversity detection, which are crucial in understanding the diversity of human faces. Kairos’ FRS is great for enterprises looking to integrate facial recognition into their system with API.
There are different price ranges for companies interested in having this software up and running via the cloud. For on-premise use, contact the vendor.
Sky Biometry is a biometric API provider that offers enterprises AI-powered facial recognition and detection services. Facial recognition, attribute determination and face detection are at the core of their services.
Sky Biometry is capable of applying facial landmarks to determine gender and age, check for facial mood and detect if there are objects on your face. The Sky Biometry service is most suitable for enterprises with their own developers who just need to apply Sky’s FRS API to their application for facial recognition.
The tool has different subscription modes and a demo version that allows you to have a comprehensive look at the provisions of the software.
FaceFirst is a biometric security solution provider for retailers who wish to adopt AI to mitigate fraud, theft and violence in their business. With the FaceFirst security solution, you can control access, authenticate customer ID and detect age.
As a face matching system with a high degree of accuracy, FaceFirst enjoys patronage from businesses such as casinos, airports and stadiums. This category of businesses needs the software to minimize the rate of disallowed access to business premises. You can check out the product by requesting a demo or contact them for pricing details.
Face++ ensures that businesses have a facial recognition solution that goes beyond facial detection to include deeper layers of AI-powered recognition of other human attributes. Apart from liveness detection and faceID identity verification, Face++ also provides a sophisticated algorithm for skeleton detection which can help detect human body motion.
Furthermore, Face++ also provides a high level of accuracy in its identity detection and matching process. The software also prides itself on identifying images under challenging conditions, such as bad lighting and low-quality aspect ratios.
Trueface leverages deep vision technology for its facial recognition solution. The FRS serves its customers through a deployable container with an SDK and a plug-and-play mode.
Trueface’s core services include liveness verification, weapon detection, facial recognition and mask detection. Trueface offers some degree of flexibility in cloud deployment options available to customers. You can deploy in your cloud, on-premise or hybrid infrastructure to meet your needs. The solution has proven to be suitable across a wide range of industries and government agencies.
What is facial recognition software?
Facial recognition software is a biometric security technology that matches human faces to an existing system database of images or videos to confirm human identities. It is software designed to authenticate human identities using image detection, analysis and recognition.
Facial recognition software requires an artificially intelligent algorithm to function properly as it is more sophisticated than other biometric security methods. All facial recognition software makes intelligent decisions to confirm human identities based on these processes: Face detection, analysis, image conversion, and matching or recognition. All these processes are processed within seconds to decide whether to grant access to a user.
How facial recognition software works
Apart from the popular use of faceID as a means in phone recognition technologies, FRS has a deeper working mechanism that everyone hoping to adopt the software in their organization should understand.
Facial recognition software depends on the information fed to the database component of the software to recognize identities. In this case, this information could be photos or videos. Generally, all facial recognition software operates according to the steps listed below:
This is the first step in the facial recognition process. At this point, the camera detects the facial representation of the image being verified. To detect a face, the software checks certain features on the human face that can hardly be distorted out of recognition with age. These features may include the depth of the eye socket, the size of the eyeball, and the distance between the eye and the nose. All these features are also referred to as the human facial landmark.
Once this facial image is detected, the software can begin analyzing the image. In the face analysis phase, the software analyzes the image and tries to match it against the faceprints already stored on the software database. Several software solutions work with 2D images, as they are easier to process during the matching process.
In trying to analyze and match the image, the facial recognition software also takes note of facial angles, lighting, resolution and other facial landmarks that help the technology in facial biometric analysis.
Image to data conversion and matching
Facial recognition software works with a sophisticated algorithm; hence, it transforms images into a set of digital data based on the features captured on the facial landmarks. Once the facial features are converted to data, the biometric technology will interpret this data set and compare it with the faceprints in the software database. Everyone has a unique face print, just like our fingerprint, and that’s how the software can tell the difference between many faces.
The matching process determines the type of decision the software makes. If the faceprints analyzed by the software match the ones in the system, the software grants access.
These steps highlighted above might appear like a time-consuming process. However, good facial recognition software can get this done within a few seconds.
Key features of facial recognition software
Security and user privacy
Quality facial recognition software should be able to uphold user security and privacy. Human faces are tied to some personal and valuable information. FRS should be able to encrypt user data on the system to mitigate the possibility of a data breach.
Well-trained and database expansion
The deeper the training the AI of a facial recognition software, the higher the accuracy of its facial detection and matching capability. Every facial recognition software should be able to keep expanding its database with more information to accommodate more image and video variations. Just like in machine learning, an FRS must be fed with as much information as possible to enhance its accuracy.
Algorithm precision is a major issue in facial recognition software. That’s why it’s an important feature an FRS cannot do without. For FRS to be accurate in facial detection, it should be able to cut down on its false acceptance and rejection rates. This is only possible if the software has a high-level algorithm accuracy.
Top facial recognition software should make provisions for expansion, not only in user base but in integration possibilities with other tools and deployment options.
Factors to consider before picking an FRS
Does the FRS software meet your business requirement?
Every business organization has peculiar needs they intend to meet when investing in any software. In the case of facial recognition software, you should determine your business needs and ascertain if the FRS can meet those needs. For instance, you may need the software for just internal authentication of employees that work remotely. This critical need should inform your decision when opting for an FRS, as some software offer this option more than others.
What is the accuracy rating?
You should try to determine the accuracy metrics of the FRS you intend to adopt. For example, what accuracy threshold is your business comfortable with? An answer to this question will guide you properly on what level of accuracy to expect from the software.
How secure is the FRS solution?
Data must be encrypted and protected from breaches. It should also protect user privacy. There is a fear from some members of the public that FRS vendors could sell human data to the highest bidder. Consider checking the software vendor’s security provisions and regulatory compliance.
What are integration provisions available on the software?
Your choice of an FRS should also be determined by the integration capabilities available on the software. Therefore, if you’re in the position to adopt the software, you should ascertain if your business can be integrated into the software without any hassles.
Frequently asked questions about facial recognition software
How accurate is FRS?
The accuracy of facial recognition software can be determined by human and algorithm performance. The wider the data, the higher the accuracy. The sophistication of the software algorithm will also impact accuracy.
Does image quality impact the results of an FRS?
Yes, the quality of the picture being searched can affect the outcome of the search. Image quality, in this sense, could be about how the image was collected. Consider camera position, photo compression quality, aspect ratio, lighting and obstruction: All these factors can affect the precision of facial recognition.
How does FRS function?
The complete functionality of every facial recognition technology is hinged on three steps: Facial identification, facial recognition and matching, and the granting or denying of access.
What’s the main concern of facial recognition?
There is a concern that facial recognition databases could be hacked and used for malicious motives. Some people also argue that the database can be sold by software owners, endangering the data they are meant to secure.
Is AI/ML used in facial recognition?
Yes, for facial recognition software to function accurately, some aspects of artificial intelligence and machine learning must come to play. The end goal of an FRS lies in conducting biometric checks by comparing a life or still image to a set of preserved data that the software acquired through deep learning.