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Facial Recognition & Feature Extraction

We work with algorithms for facial recognition and feature extraction. We integrate these into various applications for authentication

Face can be scanned by cameras the minute a person enters the door/premises. Most installations rely on security personnel manning high-megapixel digital cameras to identify uninvited guests. Biometric face recognition technology is relatively new, but it has the potential to change strategic installation surveillance forever.**Two types of facial recognition biometric screening systems : **

  • Dumb Systems
  • Smart Systems

Dumb systems automatically detect human faces and grab a snapshot of every person entering the premises for later use. Smart systems do that too, but also analyze the face of each guest and compare them against the images of undesirables in the database. If the system finds a match, it alerts security.There are many potential use of this technology and we have developed algorithms for facial recognition and also algorithms for various feature extractions like smile, blinking of eye, emotions etc.We integrate our algorithms into various facial recognition applications for identification, security, beauty, loyalty management,mobile, eCommerce, online advertising, social media, travel, e-payments, e-education and authentication at various levels of transactions.**Write to us for more information

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Deploying Facial Recognition Software in India: Integration, Accuracy and Privacy

Choosing facial recognition software in India is less about the camera and more about how the match result is used downstream. In practice, faces rarely work alone. Pairing a face template with an RFID or biometric credential turns a single check into layered authentication, which is why we often pair face capture with RFID access control and biometrics or a contactless palm-vein scanner as a second factor. For workforce use, the same match event can post directly into a time and attendance system or feed employee tracking software, removing manual punch-in.

Accuracy depends on enrolment quality, lighting and camera placement far more than on the algorithm alone. Off-angle mounting, backlit doorways and low-resolution feeds cause most false rejects, so we advise site-appropriate placement and controlled enrolment images. For high-security sites such as secured premises and control rooms, a real-time matching system that flags watchlist entries is worth the extra tuning. Given India’s evolving data-protection expectations, plan for consent, on-premise template storage and retention limits from day one. Tell us your environment and volumes and we will scope a workable design — talk to our team.

Frequently asked questions

What is facial recognition software and how does it work in India?

Facial recognition software captures a face from a camera, extracts distinctive features into a mathematical template, and compares it against enrolled records to verify or identify a person. In India it is commonly used for access control, attendance, visitor management and watchlist alerting. Accuracy depends heavily on enrolment quality, camera placement and lighting rather than the algorithm alone.

Can facial recognition software be integrated with RFID and biometric access control?

Yes. We integrate facial recognition with RFID cards and biometric factors such as palm-vein scanning so a doorway can require both a face match and a credential. This layered approach reduces spoofing risk and suits high-security sites. The match result can also trigger gates, log attendance or update tracking software automatically.

What is the difference between a dumb and a smart facial recognition system?

A dumb system detects faces and stores a snapshot of everyone entering for later reference. A smart system additionally compares each face against a database in real time and alerts security when it finds a match against a watchlist. Smart systems need more careful tuning of camera placement and enrolment images to keep false alerts low.

What affects the accuracy of facial recognition software?

Enrolment image quality, camera resolution, mounting angle and lighting are the biggest factors. Backlit doorways, off-angle cameras and low-resolution feeds cause most false rejections. Good site design, controlled enrolment photos and appropriate camera placement typically matter more than which recognition algorithm is used.

How should facial recognition data be stored and protected?

Face templates are sensitive personal data, so plan for user consent, on-premise or controlled template storage, access restrictions and defined retention limits from the outset. Given India's evolving data-protection expectations, we recommend designing privacy safeguards into the deployment rather than adding them later. Contact us to scope a compliant setup for your site.

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Talk to our RFID specialists — we manufacture in India and ship nationwide.