Report Outline

Report Outline
Biometric Recognition of face recognition is separated with chapter for better overview.


CHAPTER 1: INTRODUCTION OF FACE BIOMETRIC RECOGNITION
1.1-Introduction
1.2-Problem Statement
1.3-Objective
1.4-Scope
1.5-Thesis outline


CHAPTER 2:LITERATURE REVIEW
2.1-Introduction
2.2-Face Recognition Background
2.3-Principal Component Analysis Approach
2.3.1-Eigenvalues and Eigenvectors Problems
2.3.2-The Jacobi’s series Transformations
2.4-Artificial Neural Network
2.4.1-Architecture
2.4.2-The Activation Function
2.5-Summary


CHAPTER 3:METHODOLOGY
3.1-Introduction
3.2-Preprocessing
3.2.1-Face Acquisitions
3.2.2-Change Format
3.2.3-Face Library Formation Phase
3.2.4-Training Set Acquisitions
3.3-Feature Extractions
3.3.1-Eigenvalues and Eigenvectors implementations
3.3.2-Eigenfaces Transformations
3.3.3-Dimensions Reductions
3.3.4-Feature Vectors
3.3.5-Rebuilding a Face Image
3.4-Artificial Neural Network Implementations
3.4.1-Backpropagation Algorithm
3.5-Classifier Models
3.5.1-Model A Classifier
3.5.2-Model B Classifier
3.5.3-Model C Classifier
3.6-Normalization
3.7-Cross Validation Setup
3.8-Summary


CHAPTER 4:RESULTS AND DISCUSSION
4.1-Introduction
4.2-Principal Component Analysis
4.2.1-Eigenfaces
4.2.2-Feature Extraction
4.2.3-Normalization
4.3-Training and recognition
4.4-Discussion
4.4.1-Using Different Face Images Combination
4.4.2-Using Different Normalization technique
4.4.3-Using Different Number of Eigenvectors
4.4.4-Recognize a New Face Image
4.4.5-Using Different Size of Face Images
4.4.6-Using Different Combinations of Neural Network Parameter
4.5-Graphical User Interface Model
4.6-Summary


CHAPTER 5:CONCLUSION
5.1-Introduction
5.2-Contribution
5.3-Future Works