Face Recognition Technology involves analyzing certain facial characteristics, storing them in a database and using them to identify users accessing systems. There are number of reasons to choose face recognition. Some of them are: It is non-intrusive and requires no physical interaction on behalf of the user It is accurate and allows for high enrolment and verification rates It does not require an expert to interpret the comparisons It can use your existing hardware infrastructure – existing cameras and image capture devices will work smoothly You can use existing images without having to re-enroll every user (For ID cards, passports, driver’s licenses, etc.) It is the ONLY biometric that allows you to perform passive identification in a one-to-many environment (e.g. Identifying a terrorist in a busy airport terminal)
|
Ontime Compact
(Facial Recognition Time Attendance System)

|
Why OnTime Compact?
Want to avoid buddy punching, clock padding and general inaccuracy of time capture?
Fed up of errors in capturing time manually? Or spending time doing the difficult task of consolidating data from various sources?
Would you prefer to have a system as easy to use as fingerprint but would prefer more durability, accuracy and data usability among others?
If you are a small organization and would like to have at the fastest and most accurate time and attendance system at an affordable price use Ontime Compact from Avancar Group.
Key Features
Ř Visual view of video input Ř Visual view of face detection Ř History / Enrolled / Suspects view Ř Voice alerts during system operationŘ Easy to use graphic interface Ř Fast and accurate Face verification
Employee Verification
OnTime-Compact is a Time & Attendance System with a Face recognition System, specifically designed to provide irrefutable personal verification. It is a standard, Camera and Prompt Software to enroll and verify employees, store their Face records, keep logs, and interface with computers. OnTime provides enhanced security, superior speed. Employee IN & OUT times are stored as Soft Data, This reduces the manual drudgery of Data Entry, Register maintenance and monthly requirement of Punch Cards for conventional Time Clocks to a minimum.
|
Recommended minimal image size |
640 x 480 pixels |
|
Multiple faces detection time (using 640 x 480 image) |
0.07 sec. |
|
Single face processing time (after detecting all faces) |
0.13 sec. |
|
Matching speed |
100,000 faces/sec. |
|
Size of one record in the database |
2.3 Kbytes |
|
Maximum database size |
unlimited |
Software Specifications
• Facial Recognition customizable engine • Generic video interface (Win 32 API) • Real time facial detection • Real time facial matching • Enhanced matching mechanism (Matching attempts) • Adjustable image processing • User Management / Time Zones • Time Attendance feature (In / Out) (Reasons) • Fully customable Time Attendance • Log Browser including visual history • User Privacy mode - no image savings
Hardware Specifications:
Device:
7" LCD Display, Internal Video Camera, Internal Speaker, Internal Video grabber
System Requirement
Pentium 4 1.66GHZ , 512MB RAM (Minimal) , 20GB Free HD , USB 2.0
Employee database maintains
information’s like..
Face Id, Full Name, Job Description, Supervisor Name, Valid Upto, Customizable shift timings
SOFTWARE INTERFACE
Facial Recognition Adjustable Attributes
• Minimal Similarity Level • Eye distance • Matching attempts • Face sample rate
Other Advantages
• Work hours, tardiness absence, vertime report by individual by user defined time period
• Time & Attendance data modification by manager
• Data export facility for other system cooperation with ERP, payroll etc.
Face Recognition
Humans mostly use faces to recognize individuals. Advances in computing capability now enables similar recognition automatically. Early face recognition algorithms used simple geometric models, but the recognition process has now matured into a science of sophisticated mathematical representations and matching processes. Major developments have propelled face recognition technology into the spotlight.
Face recognition can be used for both verification (1:1), and Identification (1:N) applications.
Face Template
The heart of the facial recognition system is the Local Feature Analysis (LFA) algorithm. This is the mathematical technique the system uses to encode faces. The system maps the face and creates a "template", a unique numerical id for that face.
Once the system has stored a "template", it can compare it to the thousands or millions of "templates" stored in a database.
Each template occupies only 2.3 KB of data.
Identification vs. Verification
Verification (1:1, one-to-one) - The process of determining a person's identity by performing matches against one biometric template that is located upon known ID. 1:1 verification usually uses tokens like: Card, code, or any other key based indexing. Identification (1:N, one-to-many) - The process of determining a person's identity by performing matches against multiple biometric templates. Identification systems are designed to determine identity based solely on biometric information. here are two types of identification systems: positive identification and negative identification.Our advanced applications allow our customer full control over recognition method. We support both 1:1 (verification) an 1:N (identification) methods.
Some thoughts and imaginations are fashionable, instilled with inspiration. to uphold innovation is interesting. Smart ideas are meant to realize and execute. The execution of idea needs Logic. AVANCAR security & Access Services Pvt Ltd is on the podium to keep up a global outlook in the development of software products and services.