Modeling 3-dimensional image from a2-dimensional image using OpenGL

The main objective of the project is to study on the process of transferring twodimensional (2D) image into a three-dimensional (3D) object by using OpenGL. Other than that, this project also covers onthe research that involves jaggedness of a 3D image. From the research made, the outcome product...

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Bibliographic Details
Main Author: Mohamed Shuhidan, Shuhaida
Format: Final Year Project
Language:English
Published: Universiti Teknologi Petronas 2004
Subjects:
Online Access:http://utpedia.utp.edu.my/8624/1/2004%20-%20Modeling%20of%20N2%20Seperation%20from%20Natural%20Gas%20Using%20Alumina%20Membrane.pdf
http://utpedia.utp.edu.my/8624/
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Institution: Universiti Teknologi Petronas
Language: English
Description
Summary:The main objective of the project is to study on the process of transferring twodimensional (2D) image into a three-dimensional (3D) object by using OpenGL. Other than that, this project also covers onthe research that involves jaggedness of a 3D image. From the research made, the outcome product will be 99% free from jaggedness. This kind of practice will maximize the performance of the product in terms of the efficiency. The project is put into practice in order to decrease the cost in producing a threedimensional image from its corresponding two-dimensional image. At present, the commonly used tools to model a three-dimensional image are quite costly and expensive. Moreover, these tools such as digitized scanner are quite bulky and immobile. The project scope of study will only be within the Computer Graphic and Computer Vision area. A single two-dimensional image does not contain depth value and this will certainly make the image lack of realism. In contrast, the depth value needs to be added in the process of modeling a three-dimensional image from a two-dimensional image. This project includes reading the depth value of a two-dimensional image. These values will be manipulated and assigned as the depth value of the three-dimensional image. Then, each point identified and connected by a triangle. The combination of the triangles will produce a smooth surface of a three-dimensional image. This process will be repeated to another image in order to optimize the smoothness of the three-dimensional image. Lastly, factors that influenced the smoothness of the created three-dimensional model will be identified.