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A novel hybrid edge detection algorithm based on wavelet thresholding and ICA

International Conference on Man Machine Systems (ICoMMS 2012) organized by School of Mechatronic Engineering, co-organized by The Institute of Engineer, Malaysia (IEM) and Society of Engineering Education Malaysia, 27th - 28th February 2012 at Bayview Beach Resort, Penang, Malaysia.

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Bibliographic Details
Main Authors: Moslem Taghizadeh, Mahboobeh Hajipoor
Other Authors: taghizadeh.uni@gmail.com
Format: Working Paper
Language:English
Published: Universiti Malaysia Perlis (UniMAP) 2012
Subjects:
Independent component analysis
Edge detection
Shrinkage function
Poisson noise
Online Access:http://dspace.unimap.edu.my/xmlui/handle/123456789/20576
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spelling my.unimap-205762012-08-03T08:53:40Z A novel hybrid edge detection algorithm based on wavelet thresholding and ICA Moslem Taghizadeh Mahboobeh Hajipoor taghizadeh.uni@gmail.com ma.hajipoor@gmail.com Independent component analysis Edge detection Shrinkage function Poisson noise International Conference on Man Machine Systems (ICoMMS 2012) organized by School of Mechatronic Engineering, co-organized by The Institute of Engineer, Malaysia (IEM) and Society of Engineering Education Malaysia, 27th - 28th February 2012 at Bayview Beach Resort, Penang, Malaysia. We propose a robust edge detection method based on ICA-domain shrinkage1 (independent component analysis). It is known that most basis functions extracted from natural images by ICA are sparse and similar to localized and oriented receptive fields, and in the proposed edge detection method, a target image is first transformed by ICA basis functions and then the edges are detected or reconstructed with sparse components. Furthermore, by applying a shrinkage algorithm to filter out the components of noise in ICA-domain, we can readily obtain the sparse components of the original image, resulting in a kind of robust edge detection even for a noisy image with a very low SN ratio. The efficiency of the proposed method is demonstrated by experiments with some natural images. 2012-08-03T08:53:40Z 2012-08-03T08:53:40Z 2012-02-27 Working Paper http://hdl.handle.net/123456789/20576 en Proceedings of the International Conference on Man-Machine Systems (ICoMMS 2012) Universiti Malaysia Perlis (UniMAP) School of Mechatronic Engineering
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 Independent component analysis
Edge detection
Shrinkage function
Poisson noise
spellingShingle Independent component analysis
Edge detection
Shrinkage function
Poisson noise
Moslem Taghizadeh
Mahboobeh Hajipoor
A novel hybrid edge detection algorithm based on wavelet thresholding and ICA
description International Conference on Man Machine Systems (ICoMMS 2012) organized by School of Mechatronic Engineering, co-organized by The Institute of Engineer, Malaysia (IEM) and Society of Engineering Education Malaysia, 27th - 28th February 2012 at Bayview Beach Resort, Penang, Malaysia.
author2 taghizadeh.uni@gmail.com
author_facet taghizadeh.uni@gmail.com
Moslem Taghizadeh
Mahboobeh Hajipoor
format Working Paper
author Moslem Taghizadeh
Mahboobeh Hajipoor
author_sort Moslem Taghizadeh
title A novel hybrid edge detection algorithm based on wavelet thresholding and ICA
title_short A novel hybrid edge detection algorithm based on wavelet thresholding and ICA
title_full A novel hybrid edge detection algorithm based on wavelet thresholding and ICA
title_fullStr A novel hybrid edge detection algorithm based on wavelet thresholding and ICA
title_full_unstemmed A novel hybrid edge detection algorithm based on wavelet thresholding and ICA
title_sort novel hybrid edge detection algorithm based on wavelet thresholding and ica
publisher Universiti Malaysia Perlis (UniMAP)
publishDate 2012
url http://dspace.unimap.edu.my/xmlui/handle/123456789/20576
_version_ 1643793118846255104
score 13.214268

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