Project overview Face Recognition Security System Based on “Image Passport” Algorithm (FRSS)

Project 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 structure Project 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 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 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: Preparation StageStage descriptionResult Stage 1Security system conception development. Some mathematical algorithm are developed and ready for implimintation on software level. Report Project Leader Concept document development.Concept document ProgrammersLearning 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 Version StageStage descriptionResult Stage 2Alpha version FRSS is developed and some parts are ready for presentation. Report Project LeaderFull system concept.System concept. PorgrammersAlpha 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 Version StageStage descriptionResult Stage 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. ProgrammersBuild 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 StageStage descriptionResult Stage 4Beta version testing. Additional program features Report, Program Project LeaderTracking bugs. Controlling all others to follow main FRSS concept. Improving FRSS concept Report ProgrammersTesting, 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: Prerelease StageStage descriptionResult Stage 5 Completion of FRSS up to prerelease.Prerelease Project leaderComplete FRSS description. Documentation.Report ProgrammersCatching 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 Testing StageStage descriptionResult Stage 6 Final testing.Report. Bugreport. Project leaderFinal testing.Report ProgrammersElimination 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 Release StageStage descriptionResult Stage 7Complete productRelease. ProgrammersTo eliminate last bugs. Complete testing image data base. Release and demo version All others To eliminate last mathematical and algorithmical problems. Report

Calendar Plan: Chart Stage 1 Stage 2 Stage 3 Stage 4 Stage 5 Stage 6 Stage 7

Attachment 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.) 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.) 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.