Fast & accurate face recognition

• GLVQ based multiple-matching face detection
• Combination of eye-zone extraction and facial recognition
• Recognition based on neural network technology
• Short processing time, high recognition rate
• Recognition regardless of vantage point and facial changes (glasses, beard, and expression)

Reliable matching

• Optimal results through Adaptive Regional Blend Matching (ARBM) technology
• Extraction of similar facial areas
• Identification and authentication based on individual facial features
• Easy adaptation to existing IT systems
• Flexible integration into many types of video monitoring systems
• 1:n matching
• Simple connection to NEC AFIS
• Supporting diverse graphic and video formats as well as live cameras

Diverse Application Areas

NEC's biometrics face recognition process has a highly diverse range of applications, extending from crime-fighting, border control, to access control for sensitive areas.

Generalized Matching Face Detection Method (GMFD)

NEC's face recognition technology utilizes the GMFD method that provides high speed and high accuracy for facial detection and facial features extraction. The main logic for facial recognition within GMFD is a modified Generalized Learning Vector Quantization (GLVQ) algorithm, which searches and selects face area candidates after the generation of potential eye pairs. GLVQ is based on a neural network and is not easily fooled by attempts to conceal identity via the usage of caps, hats, sunglasses, etc.


NEC AFIS is the first AFIS that uses ridge counts and relationships between minutiae in its matching algorithm. This algorithm allows AFIS to match distorted prints while maintaining matching selectivity. In addition, NEC's use of "zone" data reduces the number of false minutiae by ensuring that only minutiae in "clear zone" are used in matching. These features allow NEC AFIS customers to achieve high hit rates while reducing the number of candidates to be compared with.

Perturbation Space Method (PSM)

NEC has developed the PSM algorithm that converts two-dimensional images (e.g., photographs) into three-dimensions (such a process is called "Morphing"). The three-dimensional representations of the head are then rotated in both the left-to-right and up-and-down directions. Further processing applies differing illumination across the face, which greatly enhanced the chances of a query "faceprint" for matching against its true mate from the database.

Adaptive Regional Blend Matching (ARBM) Method

Thanks to the PSM algorithm, the general range of facial poses and illumination has ceased to present major problems. However, the range of variation of different facial parts is still a challenge.


To reduce the impact of adverse local changes (e.g., varying facial expression caused by smiling and blinking eyes, and intentional changes caused by the wearing of caps, hats and glasses), NEC's face recognition technology utilizes the ABRM algorithm, which reduces the impact of such local changes during the matching process. The minimization of the local changes guarantees the overall face recognition accuracy.

Deployment Examples

Japan - Universal Studios Japan?：Access Control System
Your face can be a pass : An ultra user-friendly entry system is in service!