iris recognition system using principal component analysis - Dissertation Example

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iris recognition system using principal component analysis

This gives a fine demarcation between the inter class and intra class irises and hence the recognition becomes easier. Principal component analysis has been used to reduce the dimensionality. This enables choice of appropriate features from the iris templates and improves classification. The iris recognition accuracy has been described in terms of False Reject Ratio and False Accept Ratio. Table of contents Chapter 1 – Introduction of Project 1.1. Introduction 1.2. Project background 1.3. Problem Statement 1.4. Project aim and objectives 1.5. Significance of the project 1.6. Scope of project 1.7. Overview of project 2. Chapter - 2 Review of Literature 2.1. Introduction 2.2. Human Iris System 2.2.1. Iris and Biometrics 2.2.2. Artificial Intelligence for Iris recognition 2.3. Scanning the Iris 2.3.1 Localization of Landmarks 2.3.2 Digital Imaging 2.4. statistical dependence 2.5. Principal Component Analysis 2.5.1 Covariance 2.5.2 Normality and Residuals 2.6. Chapter summary Chapter 3 – Methodology and framework of the Project 3.1. Introduction 3.2. Method 3.3. Requirements 3.4. Project Design 3.5. Hardware Design 3.6. Software Design 3.7. Chapter summary Chapter 4 – Project implementation and testing 4.1. Introduction 4.2. Image Segmentation 4.3. ...Show more

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Iris recognition system using principal component analysis Abstract Iris recognition has been a challenge in the past with the recognition accuracy being low. This project has implemented an iris recognition system using image processing. The hardware arrangement consists of Raspberry Pi arm processor and the software used is MATLAB…
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