Verification of Facial Features of the Employees in FEU-EAST ASIA COLLEGE Accounting and Registrars Office Using Geometrical Features Analysis and Template Matching

Prepared for:Dr. Henry G. Magat

Prepared by: Garcia, Jessa MarieJordan, RonelReyes, EloisaVillamater, Chelsea

Date of Submission:December 13, 2013

TABLE OF CONTENTSTitle Page.......................................................................................................1Transmittal Letter...........................................................................................3IntroductionPurpose...............................................................................................4Background..........................................................................................5Scope...................................................................................................6DiscussionApproach..............................................................................................8Result...................................................................................................Statement of Work...............................................................................ResourcesPersonnel.............................................................................................Facilities/Equipment.............................................................................CostsFiscal...................................................................................................Time....................................................................................................ConclusionSummary............................................................................................Contact...............................................................................................References

To: Dr. Henry G. Magat Date: December 13, 2013Subjects: The Implementation of Facial Features Verification Using the two strategies in FEU East Asia College Accounting and Registrars OfficeDear Sir,This is to submit our proposal on Verification of Facial Features of the Employees in FEU EAST ASIA COLLEGE Using Geometrical Features and Template Matching. The completed report, which is attached, shows that the face verification system together with a main log-in and log-out system using username and password as main input will contribute in improving the security against persons who plan to access students confidential files illegally. Thank you for the chance to study this proposal. If you have any questions about the report, you can send an email to us. Yours Truly,Jessa Marie GarciaRonel JordanEloisa ReyesChelsea Villamater

1. Introduction1.1 PurposeThe question, Can a machine recognize faces at least as well as human?, it is a challenge that may have an impact in improving security system in well-defined important places. A human being can distinguish a persons face by his own unique and distinct features varying for every individual. These facial features information are stored in the human brain and will serve as base for the human to remember and recognize the person if he/she will be seen again. Through the years of mans ingenuity certain developments have been made and innovations are being introduced. One of these is Face Verification System. The study aims to simulate this human process by implementing a computer based system that will store facial features data of a face image in a database and compare it with a recently captured image of the same person. FEU East Asia College Accounting and Registrar Office handles important documents and perform sensitive transactions like accepting payments of tuition fees, processing of transcript records, etc. Thus, more defined security measures are needed. With this system assurance in every personnel will produce productivity in terms of work ethics. It is where Facial Featured Detection and Verification must be applied.

1.2 Background Automated face recognition is an interesting computer vision problem with many commercial and law enforcement applications. Researchers on this are date back to early machine vision research in 1970s. However, face recognition is still an area of active research since a completely successful approach or model has not been proposed to solve the face recognition problem.Automatic human face recognition, a technique which can locate and identify human faces automatically in an image and determine who is who from a database, is gaining more and more attention in the area of computer vision and pattern recognition over the last two decades. There are several important steps involved in this problem: detection, representation and identification. Based on different representations, various approaches can be grouped into feature-based and image-based. Feature-based approaches, especially those relying on geometrical featured, represent the face as a multidimensional feature vector and determine the identification by the Euclidean distance between different feature vectors. Image-based approaches rely on the entire image, instead of some features. In its simplest form, the face is represented as a 2D array of intensity values. The feature-based approach has the advantage over the image-based approach that it requires less data input but suffers from the incompleteness of features and difficulty of automatic feature detection. By carefully choosing the region of interest (ROI) and possibly appropriate transformations, the image-based approaches can give

more reliable results than the feature-based approach (Balasuriya & Kodikara, May 2000)1.3 ScopeThe scope of the study was to design and implement a facial features verification system that will serve as an additional security measure for the FEU- East Asia Registrar and Accounting Offices. Since technology is developing rapidly, certain risks and threats to typical security systems are also improving. Threats like technologically advance gadgets and techniques are used by modern criminals to breach security. In order for security system to catch-up with these evolving threats, additional security measures should be implemented in order to improve and tighten the security system to counter these anti-security modern ways.On the other hand, since the study is only an additional security measure, it is subjected to many limitations. First to mention is that the system in only focused on processing expressionless face images. Parameters that best describe an expressionless face are as follows: The eyelids are widely open. The eyeballs looking in the forward direction (towards the camera). The eyebrows in a relax manner. Lips are close with the teeth not showing. The head in a straight position(most likely not tilted)Any more facial feature images that will be projected or captures differently as mentioned may affect the verification process.The face area must be visually clear and clear of things that might cover the important facial parts. In this case, hair covering the eyes, heavy cosmetics and accessories such as eyeglasses should be removed during the image capturing process.Any major changes that might occur to an employees face such as severe facial injuries, sickness or maybe an associate who would undergo a facial plastic surgery should be reported immediately to the security office for the database to be updated. Minor facial disorders changes such as pimples, small cuts, sunburn, rash, etc can be disregarded because it can not affect the verification process.In accordance with the facial conditions above, lighting conditions would also affect the face detection process. Imbalance and inadequate light source can produce unnecessary shadows in a face image, and result to an error in detection. In the case of varying lighting and shadow effects produced in different facial features, an automatic calibration of contrast settings should be done in the system during a change in environment.A different contrast setting must also be set to every sample, because different skin tones also affect the detection of facial features.With this limitations present, face verification with a wide scale of samples will not be a 100% reliable.

2. Discussion

START2.1 Approach Figure 1. System Flowchart

Enter Employee Number and Scan the Facial Features

Number DatabaseCompare to the Number Database

If an Input Employee Number = Number DatabaseReject due to incorrect Employee Number

Enhance Image F

Template Matching

EndExportImport the Profile from the number databaseReject due to unauthorized personsCompare to the Face DatabaseGeometrical Features ProcessFace Database T

If Face Verification Percentage