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Hybrid filters for edge detection and its new fuzzy performance evaluation technique

Master of Science in Engineering Mathematics

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Bibliographic Details
Main Author: Yogheswary, Kalaichelven
Other Authors: Ahmad Kadri, Junoh, Dr.
Format: Dissertation
Language:English
Published: Universiti Malaysia Perlis (UniMAP) 2018
Subjects:
Image segmentation
Computer vision
Image processing
Edge detection
Digital image processing
Edge
Online Access:http://dspace.unimap.edu.my:80/xmlui/handle/123456789/78007
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spelling my.unimap-780072023-03-06T06:56:18Z Hybrid filters for edge detection and its new fuzzy performance evaluation technique Yogheswary, Kalaichelven Ahmad Kadri, Junoh, Dr. Image segmentation Computer vision Image processing Edge detection Digital image processing Edge Master of Science in Engineering Mathematics Edge detection is an important operation in digital image processing and also very important in field of computer vision, image segmentation and object recognition. Edge is line between two corners or surface which also a significant colour transition in an image. It also can be defined as an abrupt change in intensity of pixels and discontinuity in image brightness. The primary goal of edge detection methods is to extract the important feature or information in an image. In this study seven different techniques are used to extract the edge points for two different images. The seven techniques are involved the classical edge detectors as well the hybrid of the filters such as Sobel, Prewitt, Freichen, Robert, Sobel-Prewitt, Sobel-Freichen and Robert-Freichen. Performance factors are analysed in term of qualitative and quantitative aspect. Frequency distribution is used to measure the number active pixels in edge detected images. Frequency distribution is a measurement of quantitative based on the edge maps to each other relatively through statistical evaluation. The evaluation process is all added with qualitative aspect by visual analysis in term of good localization using fuzzy logic. A set of rules based on intensity of edges such as rate of ‘missing edges’,’thick edges’ and ‘broken edges’ defined. The conventional method required the human interpretation to decide upon the detection. Finally, performance evaluation is compared using Edge detection index. The indices used in Edge Detection Index are the sum of frequency distribution and visual perception scale of an image which will be obtained from fuzzy logic. The higher value of edge detection index indicates the better the filter. Overall findings indicated hybrid of Robert Freichen outperformed other combination of gradient filters with value of 2.73 in edge detection index for image 1(Lena) and 2.65 for image 2(Mechanical parts). 2018 2023-03-06T06:53:40Z 2023-03-06T06:53:40Z Dissertation http://dspace.unimap.edu.my:80/xmlui/handle/123456789/78007 en Universiti Malaysia Perlis (UniMAP) Universiti Malaysia Perlis (UniMAP) Institute of Engineering Mathematics
institution Universiti Malaysia Perlis
building UniMAP Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Perlis
content_source UniMAP Library Digital Repository
url_provider http://dspace.unimap.edu.my/
language English
topic Image segmentation
Computer vision
Image processing
Edge detection
Digital image processing
Edge
spellingShingle Image segmentation
Computer vision
Image processing
Edge detection
Digital image processing
Edge
Yogheswary, Kalaichelven
Hybrid filters for edge detection and its new fuzzy performance evaluation technique
description Master of Science in Engineering Mathematics
author2 Ahmad Kadri, Junoh, Dr.
author_facet Ahmad Kadri, Junoh, Dr.
Yogheswary, Kalaichelven
format Dissertation
author Yogheswary, Kalaichelven
author_sort Yogheswary, Kalaichelven
title Hybrid filters for edge detection and its new fuzzy performance evaluation technique
title_short Hybrid filters for edge detection and its new fuzzy performance evaluation technique
title_full Hybrid filters for edge detection and its new fuzzy performance evaluation technique
title_fullStr Hybrid filters for edge detection and its new fuzzy performance evaluation technique
title_full_unstemmed Hybrid filters for edge detection and its new fuzzy performance evaluation technique
title_sort hybrid filters for edge detection and its new fuzzy performance evaluation technique
publisher Universiti Malaysia Perlis (UniMAP)
publishDate 2018
url http://dspace.unimap.edu.my:80/xmlui/handle/123456789/78007
_version_ 1772813088861454336
score 13.18916

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