ABSTRACT

Face recognition and detection is one of the most important fields of the modern applications. Face recognition system uses two subsystems named face detection system and image database system. Face recognition can be of feature based and image based. Feature based method uses features like skin color, eyes, nose and mouth to detect and recognize human face whereas image based method utilizes some preprocessed image sets for detection. The project implements feature based face recognition system which first finds any face or faces in the color image and then matches it against the database to recognize the individuals. Here, the skin color pixels are used to filter out the interesting regions of human skin from other non interesting regions. Once the skin regions are located, facial features like mouth, eyebrow and nose are extracted to locate the human face. Then, the detected face from image will be compared with the database of training images to find a match. The project is implemented using Visual Basic and Microsoft Access for database management.

CHAPTER ONE

1.0INTRODUCTION

1.1 THE OVERVIEW OF THE STUDY

Face recognition has gained substantial attention over in past decades due to its increasing demand in security applications like video surveillance and biometric surveillance. Modern facilities like hospitals, airports, banks and many more another organizations are being equipped with security systems including face recognition capability. Despite of current success, there is still an ongoing research in this field to make facial recognition system faster and accurate. The accuracy of any face recognition system strongly depends on the face detection system. The stronger the face detection system the better the recognition system would be. A face detection system can successfully detect human face from a given image containing face/faces and from live video involving human presence. The main methods used in these days for face detection are feature based and image based. Feature based method separates human features like skin color and facial features whereas image based method used some face patterns and processed training images to distinguish between face and non faces. Feature based method has been chosen because it is faster than image based method and its implementation is far more simplified. Face detection from an image is achieved through image processing. Locating the faces from images is not a trivial task; because images not just contain human faces but also nonface objects in clutter scenes. Moreover, there are other issues in face recognition like lighting conditions, face orientations and skin colors. Due to these reasons, the accuracy of any face recognition system cannot be 100.

OBJECTIVES OF THE STUDY

The objective of this project is to implement a face recognition system which first detects the faces present in either single image frames; and then identifies the particular person by comparing the detected face with image database or in the both image frames.

Many limitations encountered, were in the process of gathering information for the development of this project work to this extent. It was not an easy one, so many constraints were encountered during the collection of data.

The limitation focuses of the following constraints;

i. FINANCIAL CONTRAINTS: the cost of sourcing for information and data that are involved in this work is high in the sense that we all know that information is money.

ii.TIME: A lot of time was involved in writing and developing this work,

iii.Irregularities in power supply also dealt harshly with the researcher.

1.7Definition of terms.

Analysis: Breaking a problem into successively manageable parts for individual study.

Attribute: A data item that characterize an object

Data flow: Movement of data in a system from a point of origin to specific destination indicated by a line and arrow

Data Security: Protection of data from loss, disclosure, modification or destruction.

Design: Process of developing the technical and operational specification of a candidate system for implements.

File: Collection of related records organized for a particular purpose also called dataset.

Flow Chart: A graphical picture of the logical steps and sequence involved in a procedure or a program.

Form: A physical carrier of data of information

Implementation: In system developmentphase that focuses on user training, site preparation and file conversion for installing a candidate system.

Maintenance: Restoring to its original condition

Normalization: A process of replacing a given file with its logical equivalent the object is to derive simple files with no redundant elements.

Operation System: In database machine based software that facilitates the availability of information or reports through the DBMS.

Password: Identity authenticators a key that allow access to a program system a procedure.

Record: A collection of aggregates or related items of a data treated as a unit.

Source Code: A procedure or format that allow enhancements on a software package.

System: A regular or orderly arrangements of components or parts in a connected and interrelated series or whole a group of components necessary to some operation.

System Design: Detailed concentration on the technical and other specification that will make the new system operational.