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Please use this identifier to cite or link to this item: http://dspace.unimap.edu.my:80/xmlui/handle/123456789/20576

Title: A novel hybrid edge detection algorithm based on wavelet thresholding and ICA
Authors: Moslem Taghizadeh
Mahboobeh Hajipoor
???metadata.dc.contributor.url???: taghizadeh.uni@gmail.com
Keywords: Independent component analysis;Edge detection;Shrinkage function;Poisson noise
Issue Date: 27-Feb-2012
Publisher: Universiti Malaysia Perlis (UniMAP)
???metadata.dc.publisher.department???: School of Mechatronic Engineering
Series/Report no.: Proceedings of the International Conference on Man-Machine Systems (ICoMMS 2012)
Abstract: 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.
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.
URI: http://hdl.handle.net/123456789/20576
Appears in Collections:Conference Papers

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