Object Shape Recognition Using Wavelet Descriptors

The wavelet transform is a well-known signal analysis method in several engineering disciplines. In image processing and pattern recognition, the wavelet transform is used in many applications for image coding as well as feature extraction purposes. It can be used to describe a given object shape by...

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Main Author: Adnan Abou Nabout
Format: Article
Language:English
Published: Wiley 2013-01-01
Series:Journal of Engineering
Online Access:http://dx.doi.org/10.1155/2013/435628
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author Adnan Abou Nabout
author_facet Adnan Abou Nabout
author_sort Adnan Abou Nabout
collection DOAJ
description The wavelet transform is a well-known signal analysis method in several engineering disciplines. In image processing and pattern recognition, the wavelet transform is used in many applications for image coding as well as feature extraction purposes. It can be used to describe a given object shape by wavelet descriptors (WD). Thus, it is used to recognize objects according to their contour shape by deriving a number of WD and comparing them with the WD of stored contour patterns. For our method, we use a periodical angle function derived from an extracted object contour. In order to apply the WD, the Mexican Hat can be used as the mother wavelet. In this paper, the method of object shape recognition using wavelet descriptors is described coherently and includes details relating to the method of applying the periodical angle function and the derivation of the formulas for the Haar as well as Mexican Hat wavelet descriptors. To evaluate the results of object recognition when using wavelet descriptors taking into account the dependence on the starting point, the paper describes a sufficient method for the comparison of wavelet descriptors using the minimum distance matrix.
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issn 2314-4904
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publishDate 2013-01-01
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spelling doaj-art-721f26926dcd42d2b740429a216460412025-02-03T01:09:46ZengWileyJournal of Engineering2314-49042314-49122013-01-01201310.1155/2013/435628435628Object Shape Recognition Using Wavelet DescriptorsAdnan Abou Nabout0Faculty of Electrical, Information and Media Engineering, University of Wuppertal, Rainer-Gruenter-Str. 21, 42119 Wuppertal, GermanyThe wavelet transform is a well-known signal analysis method in several engineering disciplines. In image processing and pattern recognition, the wavelet transform is used in many applications for image coding as well as feature extraction purposes. It can be used to describe a given object shape by wavelet descriptors (WD). Thus, it is used to recognize objects according to their contour shape by deriving a number of WD and comparing them with the WD of stored contour patterns. For our method, we use a periodical angle function derived from an extracted object contour. In order to apply the WD, the Mexican Hat can be used as the mother wavelet. In this paper, the method of object shape recognition using wavelet descriptors is described coherently and includes details relating to the method of applying the periodical angle function and the derivation of the formulas for the Haar as well as Mexican Hat wavelet descriptors. To evaluate the results of object recognition when using wavelet descriptors taking into account the dependence on the starting point, the paper describes a sufficient method for the comparison of wavelet descriptors using the minimum distance matrix.http://dx.doi.org/10.1155/2013/435628
spellingShingle Adnan Abou Nabout
Object Shape Recognition Using Wavelet Descriptors
Journal of Engineering
title Object Shape Recognition Using Wavelet Descriptors
title_full Object Shape Recognition Using Wavelet Descriptors
title_fullStr Object Shape Recognition Using Wavelet Descriptors
title_full_unstemmed Object Shape Recognition Using Wavelet Descriptors
title_short Object Shape Recognition Using Wavelet Descriptors
title_sort object shape recognition using wavelet descriptors
url http://dx.doi.org/10.1155/2013/435628
work_keys_str_mv AT adnanabounabout objectshaperecognitionusingwaveletdescriptors