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Introduction

Image inpainting is a technique used in the field of computer vision to fill in missing or corrupted parts of an image, making it appear as though the missing portion was never there. Inpainting can be used for various applications such as object removal, image completion, and image restoration. This thesis focuses on image inpainting for object removal and completion, where the goal is to remove unwanted objects from an image and fill in the missing regions seamlessly.

Chapter 1

1.1 Introduction
1.2 Background of study
1.3 Problem Statement
1.4 Objective of study
1.5 Limitation of study
1.6 Scope of study
1.7 Significance of study
1.8 Structure of the Thesis
1.9 Definition of terms

Chapter 2 – Literature Review

2.1 Introduction to Image Inpainting
2.2 History of Image Inpainting
2.3 Techniques for Image Inpainting
2.4 Applications of Image Inpainting
2.5 Challenges in Image Inpainting
2.6 Recent Advances in Image Inpainting
2.7 Comparison of Image Inpainting Methods
2.8 Evaluation Metrics for Image Inpainting
2.9 Future Directions in Image Inpainting
2.10 Summary of Literature Review

Chapter 3 – System Design and Methodology

3.1 Introduction to System Design
3.2 Data Collection and Preprocessing
3.3 Image Inpainting Algorithms Selection
3.4 Implementation of Inpainting Algorithms
3.5 Evaluation of Inpainting Results
3.6 Performance Metrics
3.7 Parameter Tuning
3.8 System Validation
3.9 Comparative Analysis with Existing Systems
3.10 Summary of System Design and Methodology

Chapter 4 – System Implementation

4.1 Introduction to System Implementation
4.2 Software Development Tools
4.3 Implementation of Image Inpainting Algorithms
4.4 User Interface Design
4.5 Testing and Debugging
4.6 System Optimization
4.7 Deployment and Maintenance
4.8 System Performance Analysis
4.9 Case Studies
4.10 Summary of System Implementation

Chapter 5 – Conclusion and Summary

5.1 Summary of Findings
5.2 Contributions of the Study
5.3 Implications of the Study
5.4 Future Research Directions
5.5 Conclusion

Thesis Overview on Image Inpainting for Object Removal and Completion

Image inpainting is an essential technique in computer vision for removing unwanted objects from images and completing missing regions seamlessly. This thesis focuses on image inpainting for object removal and completion, aiming to fill the gap in the existing literature on this topic. In the following chapters, we will delve into the background of the study, the problem statement, the objectives of the study, and the significance of the research. We will also discuss the limitations and scope of the study to provide a clear roadmap for the thesis.

The literature review chapter will provide an overview of the existing techniques for image inpainting, the challenges faced in this field, and the recent advances that have been made. This chapter will also include a comparison of different inpainting methods, evaluation metrics used to assess their performance, and future research directions in this area.

The system design and methodology chapter will detail the process of data collection and preprocessing, the selection and implementation of inpainting algorithms, and the evaluation of results using performance metrics. We will also discuss the parameter tuning, system validation, and comparative analysis with existing systems.

In the system implementation chapter, we will delve into the software development tools used, the design of the user interface, testing and debugging processes, system optimization, and performance analysis. This chapter will also include case studies to demonstrate the effectiveness of the proposed system.

Finally, the conclusion and summary chapter will provide a comprehensive summary of the findings, the contributions of the study, the implications of the research, and future research directions in the field of image inpainting for object removal and completion. This thesis aims to contribute to the advancement of this technology and provide valuable insights for researchers and practitioners in the field of computer vision.

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