Special effect processing of photographs
In this project, we conducted research and testing for facial retouching to treat imperfections such as wrinkles, scars and hyperpigmentation. Various colour spaces have been considered to accurately generate the skin mask and effectively segment the skin areas from the non-skin ones. Face detection...
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2021
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sg-ntu-dr.10356-1502432023-07-07T18:19:43Z Special effect processing of photographs Muhammad Haikal Mohd Rizan Anamitra Makur School of Electrical and Electronic Engineering EAMakur@ntu.edu.sg Engineering::Electrical and electronic engineering In this project, we conducted research and testing for facial retouching to treat imperfections such as wrinkles, scars and hyperpigmentation. Various colour spaces have been considered to accurately generate the skin mask and effectively segment the skin areas from the non-skin ones. Face detection has also been employed to facilitate working on the face specifically, without affecting the regions beyond it. To attain subtle and natural-looking results, different blurring filters were tested – Mean, Median and Gaussian Smoothing. The results obtained show that the proposed methods have the ability to enhance facial beautification. The structure of the report is as follows: Chapter 1 introduces the need for beautification computational techniques. Chapter 2 delves into the research behind the algorithms and techniques developed. Chapters 3-6 describe in detail the proposed facial retouching and background blur methods, the implementation, and results. Chapter 7 shows the GUI created to enable facial retouching. Lastly, Chapter 8 summarizes the key contributions of this project and potential works. Keywords: Skin Segmentation, Image Processing, Blurring, Face Detection, MATLAB, Facial Retouching Bachelor of Engineering (Information Engineering and Media) 2021-06-13T07:12:14Z 2021-06-13T07:12:14Z 2021 Final Year Project (FYP) Muhammad Haikal Mohd Rizan (2021). Special effect processing of photographs. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/150243 https://hdl.handle.net/10356/150243 en A3011-201 application/pdf Nanyang Technological University |
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Engineering::Electrical and electronic engineering Muhammad Haikal Mohd Rizan Special effect processing of photographs |
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In this project, we conducted research and testing for facial retouching to treat imperfections such as wrinkles, scars and hyperpigmentation. Various colour spaces have been considered to accurately generate the skin mask and effectively segment the skin areas from the non-skin ones. Face detection has also been employed to facilitate working on the face specifically, without affecting the regions beyond it. To attain subtle and natural-looking results, different blurring filters were tested – Mean, Median and Gaussian Smoothing. The results obtained show that the proposed methods have the ability to enhance facial beautification. The structure of the report is as follows: Chapter 1 introduces the need for beautification computational techniques. Chapter 2 delves into the research behind the algorithms and techniques developed. Chapters 3-6 describe in detail the proposed facial retouching and background blur methods, the implementation, and results. Chapter 7 shows the GUI created to enable facial retouching. Lastly, Chapter 8 summarizes the key contributions of this project and potential works.
Keywords: Skin Segmentation, Image Processing, Blurring, Face Detection, MATLAB, Facial Retouching |
author2 |
Anamitra Makur |
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Anamitra Makur Muhammad Haikal Mohd Rizan |
format |
Final Year Project |
author |
Muhammad Haikal Mohd Rizan |
author_sort |
Muhammad Haikal Mohd Rizan |
title |
Special effect processing of photographs |
title_short |
Special effect processing of photographs |
title_full |
Special effect processing of photographs |
title_fullStr |
Special effect processing of photographs |
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Special effect processing of photographs |
title_sort |
special effect processing of photographs |
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Nanyang Technological University |
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2021 |
url |
https://hdl.handle.net/10356/150243 |
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1772825126888275968 |