Project overviewProject overview

Face Recognition Security System Based on “Image Passport”

Algorithm (FRSS)

Face Recognition Security System Based on “Image Passport”

Algorithm (FRSS)

Project targetsProject targets

Target of this project is creating security system based on face recognition algorithm.

Development will take 1 years.

Target of this project is creating security system based on face recognition algorithm.

Development will take 1 years.

Organization structureOrganization structureProject Leader

Prof.Dr.

Lead Programmer-1

Programmers 2 ppl

Research conlultant-1

Dr.

Research conlultant-2

Dr.

Lead Programmer-1

Programmers 2 ppl

Usability Design Consultant (?)

Other expensesOther expenses

Other expenses: equipment (for example, particular type of video camera, software, etc.)

On stage 4-5 we will recommend to hire consultant in usability design for 2-3 consultation in order to improve interface design.

Other expenses: equipment (for example, particular type of video camera, software, etc.)

On stage 4-5 we will recommend to hire consultant in usability design for 2-3 consultation in order to improve interface design.

Calendar planCalendar plan

First stage: Preparations – 2-3 weeks. Second stage. Alpha version –3 months. Third stage. Beta version – 2.5 months. Fourth stage. Beta testing – 1 month. Fifth stage.Prerelease – 2 months. Sixth stage. Final testing – 1 month. Seventh stage. Master release – 2-3 months.

First stage: Preparations – 2-3 weeks. Second stage. Alpha version –3 months. Third stage. Beta version – 2.5 months. Fourth stage. Beta testing – 1 month. Fifth stage.Prerelease – 2 months. Sixth stage. Final testing – 1 month. Seventh stage. Master release – 2-3 months.

Extra...

This is not final version of plan and it can be changed after budget approval.

First stage: PreparationFirst stage: Preparation

Stage Stage description Result

Stage 1 Security system conception development. Some mathematical algorithm are developed and ready for implimintation on software level.

Report

Project Leader

Concept document development. Concept document

Programmers Learning engine capabilities and functionality. Initial porgramm modules are programmed and tested. Creating of testing image data base.

Report. Image data base.

Research Consultants

To develop mathematical and algorithmic details of the FRSS at a level sufficient for implementation in software (program source code) during the subsequent stages

Report, Algorithms

Second stage: Alpha VersionSecond stage: Alpha VersionStage Stage description Result

Stage 2 Alpha version FRSS is developed and some parts are ready for presentation.

Report

Project Leader Full system concept. System concept.

Porgrammers Alpha version is developed and some parts are ready for presentation. Code documentation. Creating of testing image data base.

Report: Program, code documentation

Research Consultant

To develop mathematical and algorithmic details of the FRSS at a level sufficient for implementation in software (program source code) during the subsequent stages

Report, Algorithms.

Third stage: Beta VersionThird stage: Beta VersionStage Stage description ResultStage 3 Beta version FRSS is developed and ready for

the presentation purposes. Operational/source code of FRSS-Beta is fully documented, such as any computer programmer unfamiliar with the code can modify and maintain it.

Report, Demo, Program code documentation

Project Leader FRSS complete concepte and arhitecture. Report.

Programmers Build of demo version. Creating of testing image data base.

Report

Research Consultant

Helping project leader and programmers tracking bugs and solving appearing mathematical and algorithmical problems

Report

Fourth stage: Beta Testing Fourth stage: Beta Testing Stage Stage description Result

Stage 4 Beta version testing. Additional program features

Report, Program

Project Leader Tracking bugs. Controlling all others to follow main FRSS concept. Improving FRSS concept

Report

Programmers Testing, improving, searching bugs. Working on interface design. Usability design testing.

Report, Program

Research conlultant

Helping project leader and programmers tracking bugs and solving appearing mathematical and algorithmical problems

Report

Fifth stage: PrereleaseFifth stage: PrereleaseStage Stage description Result

Stage 5 Completion of FRSS up to prerelease. Prerelease

Project leader Complete FRSS description. Documentation. Report

Programmers Catching of all possible bugs and development of FRSS up to prerelease version. Interface design. Usability design testing.

Report

Research consultant

Helping project leader and programmers tracking bugs and solving appearing mathematical and algorithmical problems

Report, algorithms

Sixth stage: Final TestingSixth stage: Final TestingStage Stage description Result

Stage 6 Final testing. Report. Bugreport.

Project leader Final testing. Report

Programmers Elimination of last bugs. Final release.

Research consultant

Helping project leader and programmers tracking bugs and solving appearing mathematical and algorithmical problems

Report, algorithms.

Seventh stage: Master ReleaseSeventh stage: Master Release

Stage Stage description Result

Stage 7 Complete product Release.

Programmers To eliminate last bugs. Complete testing image data base.

Release and demo version

All others To eliminate last mathematical and algorithmical problems.

Report

Calendar Plan: ChartCalendar Plan: Chart

01.06 02.06 03.06 04.06 05.06 06.06 07.06 08.06 09.06 10.06 11.06 12.06

Stage 1

Stage 2

Stage 3

Stage 4

Stage 5

Stage 6

Stage 7

Attachment 1: FRSSAttachment 1: FRSS

FRSS is an automated system of face video-capture, recognition and identification of person. The FRSS scans of observed scene and stores face images of every person passing camera. It analyzes and authenticates input data, calculates invariant features of input face, compares calculated features of input face with features of template faces stored at database and recognizes a person.

Face recognition technologies

The technology of biometric identification of a person by face image is based on algorithms of recognition and comparison of images. The algorithms are based on a modified method of independent components analysis (ICA). It requires calculation of maximally independent features specific for images of human faces.

The system receives digitized video image. Special-purpose algorithms search for a face image, outline it, define exact locations of eyes, position the image and normalize it with respect to perspective transformations. Then the system automatically codes the selected face image for the purpose of definition of the major specific invariant features. Then, the biometric identification system gives out a list of face images with a maximum similarity with the person. The list is sorted by correlation rate of appropriate vectors. In case the index of vector correlation is high and exceeds a specified peak value, it is

possible to consider the person being identified.

FRSS is an automated system of face video-capture, recognition and identification of person. The FRSS scans of observed scene and stores face images of every person passing camera. It analyzes and authenticates input data, calculates invariant features of input face, compares calculated features of input face with features of template faces stored at database and recognizes a person.

Face recognition technologies

The technology of biometric identification of a person by face image is based on algorithms of recognition and comparison of images. The algorithms are based on a modified method of independent components analysis (ICA). It requires calculation of maximally independent features specific for images of human faces.

The system receives digitized video image. Special-purpose algorithms search for a face image, outline it, define exact locations of eyes, position the image and normalize it with respect to perspective transformations. Then the system automatically codes the selected face image for the purpose of definition of the major specific invariant features. Then, the biometric identification system gives out a list of face images with a maximum similarity with the person. The list is sorted by correlation rate of appropriate vectors. In case the index of vector correlation is high and exceeds a specified peak value, it is

possible to consider the person being identified.

Attachment 1: FRSS (cont.)Attachment 1: FRSS (cont.)FRSS Features

Face detection, segmentation and database storage

Feature Extraction

Person identification Operative notification by preset schemes - for instance, in case a captured face

is similar to an image of a criminal stored at the database Quality transfer of video data via low-bandwidth communication channels High level of access control and automated management: every access attempt,

including unauthorized, are registered by the module Compact backup archives containing large volumes of data Export of specified images Export, printing and transfer of images Support of external execution devices Registration of all events (movements, changes of background) Flexible choice of recording modes - for instance, registration of faces stored

at the database Sorting and search of events by date, time and type Simultaneous playback, recording and search of backup data

FRSS Features

Face detection, segmentation and database storage

Feature Extraction

Person identification Operative notification by preset schemes - for instance, in case a captured face

is similar to an image of a criminal stored at the database Quality transfer of video data via low-bandwidth communication channels High level of access control and automated management: every access attempt,

including unauthorized, are registered by the module Compact backup archives containing large volumes of data Export of specified images Export, printing and transfer of images Support of external execution devices Registration of all events (movements, changes of background) Flexible choice of recording modes - for instance, registration of faces stored

at the database Sorting and search of events by date, time and type Simultaneous playback, recording and search of backup data

Attachment 1: FRSS (cont.)Attachment 1: FRSS (cont.)

Applications FRSS is designed for operation at public places, airports, stadiums, plants, prisons, and military sites.

Investigation and search activities. Upon recognition of a person, operator receives all available information and notifies law-enforcement authorities, if required.

Entrance and security check-points. Every person passing check-point is automatically registered at database (date, time, images). It is always possible to get later information on every person passed through.

Closed objects, requiring stronger access control measures. Traditional access control systems give intruders an opportunity of unauthorized access with false or another person's ID card. The FRSS module authenticates card holder automatically - by comparing faces with database data.

Face identification at frontier posts (by means of databases containing images of terrorists and wanted criminals), simultaneous authentication of a face with passport or ID photo.

Issuing authorities. Prevention of issue of duplicated documents, such as driver licenses, ID cards, etc.

Applications FRSS is designed for operation at public places, airports, stadiums, plants, prisons, and military sites.

Investigation and search activities. Upon recognition of a person, operator receives all available information and notifies law-enforcement authorities, if required.

Entrance and security check-points. Every person passing check-point is automatically registered at database (date, time, images). It is always possible to get later information on every person passed through.

Closed objects, requiring stronger access control measures. Traditional access control systems give intruders an opportunity of unauthorized access with false or another person's ID card. The FRSS module authenticates card holder automatically - by comparing faces with database data.

Face identification at frontier posts (by means of databases containing images of terrorists and wanted criminals), simultaneous authentication of a face with passport or ID photo.

Issuing authorities. Prevention of issue of duplicated documents, such as driver licenses, ID cards, etc.