In summary, the problem of face detection or recognition is alone not sufficient for the security of the cars, and hence eye detection of the same person is required for the system to be highly secured to give access for the car for owner or driver and deny for the intruder. A Review of journal and conference papers on face detection, recognition, eye detection, driver fatigue detection are done to summarise the techniques or methods employed, along with the outcomes and drawbacks or disadvantages. As an intruder may not manifest all symptoms of fatigue using a single detection system, a hybrid system is required to integrate the result of different systems and detect the intruder or to recognise the owner or driver with higher accuracy. When the result from both systems are positive, the hybrid system will determine that the car owner or driver is true with a high accuracy.
Inhaltsverzeichnis (Table of Contents)
- 1. INTRODUCTION
- 1.1 Introduction
- 1.2 Research problem
- 1.3 Aim and objectives
- 1.4 Justification for this research
- 1.5 Organization of the rest of the chapters
- 1.6 Summary
- 2. LITERATURE REVIEW
- 2.1 Introduction
- 2.2 Literature review
- 2.2.1 Facial Detection Methods
- 2.2.2 False Statistical Methods
- 2.2.3 Image Processing Methods
- 2.2.4 Drawbacks and disadvantages of the existing methods
- 2.3 Summary
- 3. CONCEPT DESIGN AND RESEARCH METHODOLOGY
- 3.1 Introduction
- 3.2 Investigation on material and component selection
- 3.2.1 Pre-processing
- 3.2.2 Software selection
- 3.3 Proposed methodology
- 3.4 Concept design based on fundamental engineering principles
- 3.4.1 Facial detection system
- 3.4.2 Perclos
- 3.4.3 Thresholding
- 3.4.4 Iris Recognition
- 3.4.5 GUI
- 3.5 Professional engineering practices
- 3.6 Summary
- 4. FINAL DESIGN AND SYSTEM IMPLEMENTATION
- 4.1 Introduction
- 4.2 System Implementation
- 4.2.1 Facial Detection
- 4.2.2 Image Processing
- 4.2.3 Feature Isolation
- 4.2.4 Eye State Evaluation
- 4.2.5 Mouth State Evaluation
- 4.2.6 Security Detection and Classification
- 4.2.7 Alarm System
- 4.3 Working Principle
- 4.4 Results
- 5. PROJECT FINDINGS AND TESTING
- 5.1 Testing of the Proposed Design
- 5.1.1 Classifier Detection test
- 5.1.2 Face Detection Test 2
- 5.1.3 CLAHE Test
- 5.1.4 System Speed Test
- 5.1.5 State Evaluation Test
- 5.2 Discrepancy between theoretical and experimental
- 5.3 Error and Troubleshooting
- 5.4 Comparison with Prior Researches
- 5.5 Sustainable Developemnt and Environmental
- 5.6 Project Management, Finance and Entrepreneurship
- 5.6.1 Project Management
- 5.6.2 Finance
- 5.6.3 Entrepreneurship
- 5.7 Moral Professionalism and Ethical consideration
- 5.8 Contribution of this project
- 5.8.1 Hybrid Cascade Classifier
- 5.8.2 Smaller Face Region Detection
- 5.8.3 Alarm System
- 5.8.4 Eye State Detection
- 5.1 Testing of the Proposed Design
Zielsetzung und Themenschwerpunkte (Objectives and Key Themes)
This research aims to develop a highly secure system for cars that goes beyond traditional face recognition, incorporating eye detection for enhanced security. It analyzes existing techniques and methods for face detection, recognition, and eye detection, identifying their drawbacks and limitations.
- Development of a highly secure car access system.
- Integration of face detection and eye detection for improved security.
- Analysis of existing methods and their shortcomings.
- Design and implementation of a hybrid system for robust security.
- Evaluation and testing of the proposed system.
Zusammenfassung der Kapitel (Chapter Summaries)
- Chapter 1: Introduces the research problem, outlines the aim and objectives, provides justification for the research, and describes the organization of the remaining chapters.
- Chapter 2: Reviews relevant literature on facial detection, recognition, eye detection, and driver fatigue detection, summarizing existing techniques, outcomes, and limitations.
- Chapter 3: Presents the concept design and research methodology, including material and component selection, software selection, and proposed methodology.
- Chapter 4: Details the final design and system implementation, outlining the steps involved in facial detection, image processing, feature isolation, eye state evaluation, mouth state evaluation, security detection, alarm system, and working principle.
- Chapter 5: Discusses project findings and testing, covering various tests conducted to evaluate the performance of the proposed design, including classifier detection test, face detection test, CLAHE test, system speed test, and state evaluation test.
Schlüsselwörter (Keywords)
This research focuses on car security, face detection, eye detection, hybrid system, driver fatigue detection, image processing, security detection, and alarm system.
Frequently Asked Questions
What is the main goal of the car security research?
The goal is to develop a high-security system for cars that combines face detection with eye detection to accurately distinguish owners from intruders.
Why is face recognition alone insufficient for car security?
Face recognition can have limitations; adding eye detection and iris recognition creates a hybrid system with higher accuracy and security levels.
What components are included in the proposed security system?
The system includes a facial detection system, iris recognition, eye and mouth state evaluation, and an integrated alarm system.
What is the "hybrid cascade classifier" mentioned in the project?
It is a key contribution of the research that integrates different detection systems to improve the reliability of identifying the driver.
How does the system handle driver fatigue?
The research reviews driver fatigue detection techniques, using eye state evaluation to monitor the driver's condition as part of the security and safety protocol.
What kind of tests were performed to validate the design?
Tests included classifier detection, system speed tests, CLAHE tests for image enhancement, and state evaluation tests.
- Citation du texte
- Bandar Hezam (Auteur), 2021, Development of High Security System for Cars, Munich, GRIN Verlag, https://www.grin.com/document/1357953
