DESIGN AND IMPLEMENTATION OF A COMPUTERISED FACE DETECTION AND RECOGNITION SYSTEM


CLICK HERE TO GET THE COMPLETE PROJECT »

DESIGN AND IMPLEMENTATION OF FACE DETECTION AND RECOGNITION SYSTEM

ABSTRACT:      

Face recognition and detection is one of the most important fields of the modern applications.  Face recognition system uses two sub-systems 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

TABLE OF CONTENT Cover page Title page   Approval pageDedication   Acknowledgment    Table of content    Abstract   CHAPTER ONE1.0     Introduction 1.1     Background of the research1.2    Statement of research problem 1.3     Objectives of the study1.4     Significance of the study1.5    Scope of the study1.6    Limitation of the study1.7    Definition of termsCHAPTER TWO: LITERATURE REVIEW2.0     Introduction2.1    Review of concept2.2    Review of related work2.3    Empirical Study2.4    System Architectural Framework/Structure  2.5    Summary of the reviewCHAPTER THREE: SYSTEM ANALYSIS AND DESIGN 3.1 Introduction3.5 Problem of the existing system3.2 Method of data collection3.3 Data preparation3.4 Program structure3.6 Justification for the new system3.7 System modeling3.8 System flow chat3.9 Activity diagram3.10 Program flow chart3.11 Database specification and designCHAPTER FOUR: SYSTEM TESTING AND DOCUMENTATION4.1 Introduction4.2 Program language justification4.3 Systems requirement4.4 Implementation details4.5 Procedure testing plan CHAPTER FIVE:     SUMMARY, CONCLUSION AND RECOMMENDATIONS5.1    Summary5.2    Conclusion5.3 RecommendationBibliographySource code

CHAPTER ONE1.0     INTRODUCTION    Face recognition system is an application for identifying someone from image or videos. Face recognition is classified into three stages ie)Face detection,Feature Extraction ,Face Recognition. Face detection method is a difficult task in image analysis. Face detection is an application for detecting object, analyzing the face, understanding the localization of the face and face recognition.It is used in many application for new communication interface, security etc.Face Detection is employed for detecting faces from image or from videos. The main goal of face detection is to detect human faces from different images or videos.The face detection algorithm converts the input images from a camera to binary pattern and therefore the face location candidates using the AdaBoost Algorithm. The proposed system explains regarding the face detection based system on AdaBoost Algorithm . AdaBoost Algorithm selects the best set of Haar features and implement in cascade to decrease the detection time .The proposed System for face detection is intended by using Verilog and ModelSim,and also implemented in FPGA.Face Detection System is to detect the face from image or videos. To detect the face from video or image is gigantic. In face recognition system the face detection is the primary stage. Figure 1 shows the various stages of face recognition system ie face detection, feature extraction and recognition. Now Face Detection is in vital progress in the real worldFace recognition is a pattern recognition technique and one of the most important biometrics; it is used in a broad spectrum of applications. The accuracy is not a major problem that specifies the performance of automatic face recognition system alone, the time factor is also considered a major factor in real time environments. Recent architecture of the computer system can be employed to solve the time problem, this architecture represented by multi-core CPUs and many-core GPUs that provide the possibility to perform various tasks by parallel processing. However, harnessing the current advancements in computer architecture is not without difficulties. Motivated by such challenge, this research proposes a Face Detection and Recognition System (FDRS). In doing so, this research work provides the architectural design, detailed design, and four variant implementations of the FDRS.1.1     BACKGROUND OF THE RESEARCH    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 non-face 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%.Face recognition is one of the most important biometrics methods. Despite the fact that there are more reliable biometric recognition techniques such as fingerprint and iris recognition, these techniques are intrusive and their success depends highly on user cooperation. Therefore, face recognition seems to be the most universal, non-intrusive, and accessible system. It is easy to use, can be used efficiently for mass scanning, which is quite difficult, in case of other biometrics . Also it is natural and socially accepted.Moreover, technologies that require multiple individuals to use the same equipment to capture their biological characteristics probably expose the user to the transmission of germs and impurities from other users. However, face recognition is completely non-intrusive and does not carry any such health dangers.Biometrics is a rapidly developing branch of information technology. Biometric technologies are automated methods and means for identification based on biological and behavioral characteristics of an individual. There are several advantages of biometric technologies compared to traditional identification methods. To take adequate measures against increasing security risks in modern world, countries are considering these advantages and are shifting to new generation identification systems based on biometric technologies.1.2    STATEMENT OF RESEARCH PROBLEM     Biometric systems are becoming an important element (gateway) for information security systems. Therefore biometric systems themselves have to satisfy high security requirements. Unfortunately producers of biometric technologies do not always consider security precautions. In publications regarding biometric technologies, drawbacks and weaknesses of these technologies have been discussed. Since biometrics form the technology basis for large scale and very sensitive identification systems (e.g. passports, identification cards), the problem of adequate evaluation of the security of biometric technologies is a current issue.Also, some other issues with face detection and recognition system is on individual with identical face like identical twins and others, in situation like this it is possible for the system to make mistake or error in processing the person image so as to grant access to the rightful user.1.3     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.In addition to the main objective of this research work, the researcher also went far more to add other features to the new system which are as fellow.1.    One of the objectives of this system is to design a system that will help the organization maintain a strong security in the work environment.2.    Highlight areas of vulnerability in the new system3.    Develop a ridged and secure database for the organization to enable them secure their sensitive data and records.1.4     SIGNIFICANCE OF THE STUDYThis study is primarily aimed at increasing efficiency in security, this research work will help the users in maintaining data. This system will reduce the rate of fraudulent activities as it can as well keep track of registered users and grant them access upon face recognition completion.Also the knowledge that would be obtained from this research will assist the management to grow, also this research work will also be of help to the upcoming researcher in this field of study both with the academic students on their study.1.5    SCOPE OF THE STUDY    The scope of this study covers only on face detection and recognition, accessing previous records and making matched for the data, updating of records and making delete.1.6    LIMITATION OF THE STUDY    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.1.7    DEFINITION OF TERMSAnalysis: 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 arrowData 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 informationImplementation: In system development-phase that focuses on user training, site preparation and file conversion for installing a candidate system.Maintenance: Restoring to its original conditionNormalization: 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.1.8 ORGANIZATION OF THE WORKThe project is organized in five chapters.  With introduction already being explained in chapter 1 and the whole idea of this research work presentation in chapter one, like objective of the study, statement of the research area of coverage limitation and definition of terms all this makes up the chapter one.Chapter 2; this section deals with the review of study, review of concept theories upon which this work is built on, the potential issues in the any face recognition system in the form of difference in the lighting conditions in which the same picture appears differently and the variations in skin color and pose. Chapter 3 talks about the software tools used in the project mainly related to visual basic programming language.  The methodology at which this research work will be implemented. In chapter 4 the system is implemented and presented with its analysis. Functions of the system and the operation of the system is also, in depth explained for reader understating and comprehension.The system requirement is also detailed and the platform at which the system can run on.Chapter 5 summaries the whole work done and make possible recommendation and suggest other points to be included into the work for future proposeREFERENCEP. N. Belhumeur, J. P. Hespanha, and D. J. Kriegman, "Eigenfaces vs. Fisherfaces: Recognition Using Class Specific Linear Projection", IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 19, no. 7, 1997, pp. 711-720. W. H. Press, S. A. Teukolsky and W. T. Vetterling, Numerical recipes in C: the art of scientific computing, 2nd ed., Cambridge University Press, 1992. ISBN:0-521-43108-5 I. Sajid, M.M. Ahmed, I. Taj, M. Humayun, F. Hameed, "Design of High Performance FPGA based Face Recognition System", PIERS 2008 in Cambridge, USA, 2-6 July, 2008. R. Zhang, h. Chang, " A literature survey of face recognition and reconstruction technique", Technical report, University of Texas, December, 2005. M. Turk, A. Pentland, Eigenfaces for Recognition, Journal of Cognitive Neuroscience, vol. 3, no. 1. 1991, pp. 71-86. [CrossRef] Matsumoto T., Matsumoto H., Yamada K., Hoshino S., Impact of artificial “gummy” fingers on fingerprint systems, in Optical Security and Counterfeit Deterrence Techniques IV, vol. 4677 of Proceedings of SPIE, pp. 275–289, San Jose, Calif, USA, January 2002.

.

DESIGN AND IMPLEMENTATION OF A COMPUTERISED FACE DETECTION AND RECOGNITION SYSTEM


CLICK HERE TO GET THE COMPLETE PROJECT »


TESTIMONIES FROM OUR CLIENTS


Please feel free to carefully review some written and captured responses from our satisfied clients.

  • "I love what you guys are doing, your material guided me well through my research. Thank you for helping me achieve academic success."

    Sampson, University of Nigeria, Nsukka.
  • "researchwap.com is God-sent! I got good grades in my seminar and project with the help of your service, thank you soooooo much."

    Cynthia, Akwa Ibom State University .
  • "Sorry, it was in my spam folder all along, I should have looked it up properly first. Please keep up the good work, your team is quite commited. Am grateful...I will certainly refer my friends too."

    Elizabeth, Obafemi Awolowo University
  • "Am happy the defense went well, thanks to your articles. I may not be able to express how grateful I am for all your assistance, but on my honour, I owe you guys a good number of referrals. Thank you once again."

    Ali Olanrewaju, Lagos State University.
  • "My Dear Researchwap, initially I never believed one can actually do honest business transactions with Nigerians online until i stumbled into your website. You have broken a new legacy of record as far as am concerned. Keep up the good work!"

    Willie Ekereobong, University of Port Harcourt.
  • "WOW, SO IT'S TRUE??!! I can't believe I got this quality work for just 3k...I thought it was scam ooo. I wouldn't mind if it goes for over 5k, its worth it. Thank you!"

    Theressa, Igbinedion University.
  • "I did not see my project topic on your website so I decided to call your customer care number, the attention I got was epic! I got help from the beginning to the end of my project in just 3 days, they even taught me how to defend my project and I got a 'B' at the end. Thank you so much researchwap.com, infact, I owe my graduating well today to you guys...."

    Joseph, Abia state Polytechnic.
  • "My friend told me about ResearchWap website, I doubted her until I saw her receive her full project in less than 15 miniutes, I tried mine too and got it same, right now, am telling everyone in my school about researchwap.com, no one has to suffer any more writing their project. Thank you for making life easy for me and my fellow students... Keep up the good work"

    Christiana, Landmark University .
  • "I wish I knew you guys when I wrote my first degree project, it took so much time and effort then. Now, with just a click of a button, I got my complete project in less than 15 minutes. You guys are too amazing!."

    Musa, Federal University of Technology Minna
  • "I was scared at first when I saw your website but I decided to risk my last 3k and surprisingly I got my complete project in my email box instantly. This is so nice!!!."

    Ali Obafemi, Ibrahim Badamasi Babangida University, Niger State.
  • To contribute to our success story, send us a feedback or please kindly call 2348037664978.
    Then your comment and contact will be published here also with your consent.

    Thank you for choosing researchwap.com.