Face and facial expression detection from static images / Zulfiqar @ Zulfikri Aris @ Azis

This research is a preliminary research to identify facial expression. The research objective is to detect face and facial expression from static images that contain human face. Image can be obtained from a image or from video. For the video, the image be converted to frames using FrameGrabber softw...

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Main Author:	Aris @ Azis, Zulfiqar @ Zulfikri
Format:	Thesis
Language:	English
Published:	2007
Online Access:	https://ir.uitm.edu.my/id/eprint/63722/1/63722.pdf
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id	my-uitm-ir.63722
record_format	uketd_dc
spelling	my-uitm-ir.637222024-03-25T08:06:37Z Face and facial expression detection from static images / Zulfiqar @ Zulfikri Aris @ Azis 2007 Aris @ Azis, Zulfiqar @ Zulfikri This research is a preliminary research to identify facial expression. The research objective is to detect face and facial expression from static images that contain human face. Image can be obtained from a image or from video. For the video, the image be converted to frames using FrameGrabber software. For face detection, it will use the Ranknet method is being used to extracted the image and convert to grayscale image. Then the resolution of the image is reduced due to memory constraint and to increase processing speed. The experiments have been made using Sobel Edge Detection, Canny Edge Detection, Prewitt Edge Detection and Robert Edge Detection. When experiment to detect face figure is conducted with zero threshold, Sobel Edge Detection is the best method to apply, while Canny Edge Detection detected with much noise. But if experiment conducted with 0.35 threshold, Sobel Edge Detection, Prewitt Edge Detection and Robert Edge Detection only detects less edge, while Canny Edge Detection can detect face figure properly. From this experiment. Canny Edge Detection has been proven to be the best technique for edge detection. Then using prior knowledge, the eyes and mouth regions are detected. The result of this region could be input to any pattern recognition classifier. 2007 Thesis https://ir.uitm.edu.my/id/eprint/63722/ https://ir.uitm.edu.my/id/eprint/63722/1/63722.pdf text en public degree Universiti Teknologi MARA (UiTM) Faculty of Computer and Mathematical Sciences Ibrahim, Zaidah
institution	Universiti Teknologi MARA
collection	UiTM Institutional Repository
language	English
advisor	Ibrahim, Zaidah
description	This research is a preliminary research to identify facial expression. The research objective is to detect face and facial expression from static images that contain human face. Image can be obtained from a image or from video. For the video, the image be converted to frames using FrameGrabber software. For face detection, it will use the Ranknet method is being used to extracted the image and convert to grayscale image. Then the resolution of the image is reduced due to memory constraint and to increase processing speed. The experiments have been made using Sobel Edge Detection, Canny Edge Detection, Prewitt Edge Detection and Robert Edge Detection. When experiment to detect face figure is conducted with zero threshold, Sobel Edge Detection is the best method to apply, while Canny Edge Detection detected with much noise. But if experiment conducted with 0.35 threshold, Sobel Edge Detection, Prewitt Edge Detection and Robert Edge Detection only detects less edge, while Canny Edge Detection can detect face figure properly. From this experiment. Canny Edge Detection has been proven to be the best technique for edge detection. Then using prior knowledge, the eyes and mouth regions are detected. The result of this region could be input to any pattern recognition classifier.
format	Thesis
qualification_level	Bachelor degree
author	Aris @ Azis, Zulfiqar @ Zulfikri
spellingShingle	Aris @ Azis, Zulfiqar @ Zulfikri Face and facial expression detection from static images / Zulfiqar @ Zulfikri Aris @ Azis
author_facet	Aris @ Azis, Zulfiqar @ Zulfikri
author_sort	Aris @ Azis, Zulfiqar @ Zulfikri
title	Face and facial expression detection from static images / Zulfiqar @ Zulfikri Aris @ Azis
title_short	Face and facial expression detection from static images / Zulfiqar @ Zulfikri Aris @ Azis
title_full	Face and facial expression detection from static images / Zulfiqar @ Zulfikri Aris @ Azis
title_fullStr	Face and facial expression detection from static images / Zulfiqar @ Zulfikri Aris @ Azis
title_full_unstemmed	Face and facial expression detection from static images / Zulfiqar @ Zulfikri Aris @ Azis
title_sort	face and facial expression detection from static images / zulfiqar @ zulfikri aris @ azis
granting_institution	Universiti Teknologi MARA (UiTM)
granting_department	Faculty of Computer and Mathematical Sciences
publishDate	2007
url	https://ir.uitm.edu.my/id/eprint/63722/1/63722.pdf
_version_	1804889658371342336

Face and facial expression detection from static images / Zulfiqar @ Zulfikri Aris @ Azis

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