Design and Implementation of Face Detection and Recognition System
Chapter One
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.
- 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.
- Highlight areas of vulnerability in the new system
- Develop a ridged and secure database for the organization to enable them secure their sensitive data and records.
CHAPTER TWO
LITERATURE REVIEW
INTRODUCTION
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.
This chapter focuses on the ongoing confronts in the field of the recognition and some basic concepts of image applications, empirical study, review of related study system architectural framework, challenges and the imaging concepts all will described in detail un this chapter.
REVIEW OF CONCEPT
FACE IMAGE DETECTION MODEL
Face detection is the elementary step in the face recognition system and acts as a stone to all facial analysis algorithms. Many algorithms exist to implement face detection; each has its own weaknesses and strengths. The majority of these algorithms suffer from the same difficulty; they are computationally expensive. The image is a combination of color or light intensity values. Analyzing these pixels for face detection is time consuming and hard to implement because of the enormous diversity of shape and pigmentation in the human face. Viola and Jones proposed an algorithm, called Haar-cascade Detector or called Viola-Jones, to quickly detect any object, including human faces, using AdaBoost classifier cascades that are based on Haar-like features and not pixels. Viola-Jones algorithm is widely used in various studies involving face processing because of its real-time capability, high accuracy, and availability as open-source software under the Open Computer Vision Library (OpenCV) [8]. Viola-Jones detectors can be trained to recognize any kind of a solid object, including human faces and facial features such as eyes, and mouths. OpenCV has implemented Viola-Jones and provides a pre-trained Haar-cascade for face detection.
INFORMATION MANAGEMENT
Data can be defined as individual facts or raw about something that can be organized to generate useful information for decision-making. Information is stimuli that have meaning in some contest for its receiver. When data is entered into and stored in a computer, it IS generally referred to as information.
Graham (2001) said, with the move from local application to a web based ones, also the data we created and access will need to undergo some profound changes. Data and information undergoes a management process to maintain its consistence and quality. Physical and logical security, quality assurance is emphasized to ensure rational utilization and reliability of data information.
DATABASES
According to Lane and William (2004). a database is part of data management system. They define a database as a container of data files, such as product catalogs, inventories and item/customer records. They say that every business would be a failure without a secure and reliable data management system. They further say that information systems are the hearts of most businesses worldwide, According to them. it is not easy to have a secure system, hut a system developer must ensure that this is achieved. They advise system developers to have clear subject areas, requirements and plans before they start designing the systems.
CHAPTER THREE
SYSTEM ANALYSIS AND METHODOLOGY
INTRODUCTION
The methodology which I will be applying in this research work will be an Expert Systems Methodology – ESM
This method is best for procedural step and for practical study guide. The steps are following in this method are:
- Identify the problem and design the task.
- Acquisition of knowledge and problem solving strategies. It involves the knowledge engineer, the domain knowledge expert, the knowledge base and inference rule and then interference engine.
- Design the system develop knowledge and then inference rules, natural language interferences, rule editor, heuristic search strategies, forward and backward reasoning with rules decision trees.
METHOD OF DATA COLLECTION
Procedures used in data collection and information gathering are here, outlined and analyzed. Data was carefully collated and objectively evaluated in order to define as well as ultimately provide solutions to the problems for which the research work is based.
During the research work, data collection was carried out in many places. In gathering and collecting necessary data and information needed for system analysis, two major fact-finding techniques were used in this work and they are:
- Primary source
- Secondary source
Primary source:
Primary source refers to the sources of collecting original data in which the researcher made use of empirical approach such as personal interview and questionnaires.
This involved series of orally conducted interviews with some select users. Also, some users were interviewed with a view to getting information about their opinion on how to best develop the system.
Secondary Source:
Perusals through online journals and e-books as well as visits to relevant websites, medical dictionaries and other research materials increased my knowledge and aided my comprehension of diagnostic processes.
CHAPTER FOUR
SYSTEM IMPLEMENTATION AND TESTING
The standard of the design includes:
- Implementation of an input format that will enable the user capture all the necessary data on staff employment and assessment.
- Structure a database system that will store all the information using Microsoft access.
- Implement of a well formatted output that will present information to management in a meaningful format containing necessary information.
CHAPTER FIVE
SUMMARY, CONCLUSION AND RECOMMENDATION
SUMMARY
Recognition is the process of identifying the particular person present in the image. Recognition is the most powerful and interesting application of image processing and has gained rapid success for over 30 years. Basically, the face detection system locates the face present in the image and after comparing with the database, if present, the identity of that person is revealed. For this purpose, sample images are already stored in the database.
The location of the database is set in the recognition system so that each and every image present in the database gets searched. If there is a match then the image is taken from the database and display at the output along with the face detected image. In addition, the name of the matching person will also be displayed. On the other hand, if there is no hit then image is not displayed and a no match message is rather displayed.
The method used in the recognition is the Image Search method. It simply takes an input image where a face was found and a directory of images as input. A signature is calculated for the input image. Then for each image in the search directory a signature is also calculated. Basically, the digital signature attempts to assign a unique value to each image based on the contents of the image. A distance is then calculated for each image in the search directory in relation to the input image. The distance is the difference between the signature of the source image and the signature of the image it is being checking against. The image with the smallest distance is returned as the matching image and displayed at the output.
CONCLUSION
The image face detection is implemented first and then the same system is used to detect from video sources. The recognition system has also been implemented on the image files. The accuracy of the system is achieved above 80%. The project is good at the pictures of the people of different races and colors. The project is good to detect the frontal faces present in the images files but not able to detect the side-views faces. The failure of detection on the pictures with very dark backgrounds colors are also the limitation of the system just like other systems. Overall it is a good project by which I have gained valuable knowledge of image processing and the steps required for any successful face detection. The advancement can be achieved as the future goal to make most parts of the project automated for surveillance and vision based applications.
RECOMMENDATION
The end of this research work the researcher, finds this work interesting and recommends it to any security information management institute, also, the researcher recommends that any other work to be carried out on this topic the current researcher should consider adding a real time facial recognition and voice detection to enhance the security level of this system.
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