G12-2025-Final Project

h1. About Project

h2. I. Project Overview

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.  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. 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. 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

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. Manual calibration methods are time-consuming and prone to human error. Our motivation is to develop a software-based approach that automates the alignment and blending process, ensuring seamless image projection. 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

* To develop an automated image blending system capable of merging two or more projections into a single seamless image.

* To apply *gamma correction* and *intensity modification* techniques to balance color and brightness across overlapping regions.

* To implement *alpha blending* for smooth transitions between images.

* To design and visualize the system architecture using **UML diagrams**.

* 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

* *Python (OpenCV, NumPY)*

* *Doxygen*

* *Redmine*

* *Astah*

h2. VIII. Application & Impact

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h2. IX. Limitation & Future Enhancements

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