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Yaroslav MAYDEBURA, 10/30/2025 04:01 PM

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h1. đź’ˇ About Project
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h2. I. Project Overview
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Our project focuses on developing a *high-quality image composition system* that seamlessly merges two or more projected images into a single, visually consistent display.  
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Using **Python** and **OpenCV**, we employ advanced image processing techniques such as *gamma correction*, *alpha blending*, and *intensity modification* to eliminate brightness and color mismatches between overlapping regions.  
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The project is organized into sub-teams responsible for software development, UML design, testing, and wiki management. Each member plays a key role in ensuring collaborative progress and well-structured documentation.  
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By integrating **Doxygen** for code documentation and **Redmine** for project tracking, we aim to produce a well-documented, scalable, and reproducible system for real-time image correction and blending.
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h2. II. Motivation & Problem Statement
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When using multiple projectors to display a single image, visible seams or brightness inconsistencies often occur in overlapping regions. These inconsistencies degrade image quality and make the final projection appear uneven.  
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Manual calibration methods are time-consuming and prone to human error.  
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Our motivation is to develop a software-based approach that automates the alignment and blending process, ensuring seamless image projection.  
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By leveraging the **OpenCV** library, the system can detect overlapping areas, apply brightness corrections, and blend images smoothly — eliminating the need for costly hardware-based calibration systems.
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h2. III. Objectives
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* To develop an automated image blending system capable of merging two or more projections into a single seamless image.  
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* To apply *gamma correction* and *intensity modification* techniques to balance color and brightness across overlapping regions.  
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* To implement *alpha blending* for smooth transitions between images.  
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* To design and visualize the system architecture using **UML diagrams**.  
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* To document the entire project using **Doxygen** and manage tasks via **Redmine**.
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h2. IV. Key Features
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h2. V. System Architecture
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h2. VI. Methodology and Development Process
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h2. VII. Technology Stack
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* *Python (OpenCV, NumPy)*  
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* *Doxygen*  
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* *Redmine*  
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* *Astah*  
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h2. VIII. Application & Impact
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h2. IX. Limitation & Future Enhancements
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