Banknote Image Retrieval Using Rotated QuaternionWavelet Filters

A new method of banknote image retrieval is proposed by using new set of rotated quaternion wavelet filters (RQWF) and standard quaternion wavelet transform (QWT) jointly. The robust and rotationally invariant features are extracted from QWT and RQWF decomposed sub-bands of banknote image. Three dif...
Ausführliche Beschreibung

Gespeichert in:

Autor*in:	Shan Gai [verfasserIn] Jiafeng Liu [verfasserIn] Xianglong Tang [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2011

Schlagwörter:	discrete wavelet transform (DWT) complex wavelet transform (CWT) quaternion wavelet transform (QWT) rotated quaternion wavelet filters (RQWF) feature extraction support vector machine (SVM).

Übergeordnetes Werk:	In: International Journal of Computational Intelligence Systems - Springer, 2017, 4(2011), 2
Übergeordnetes Werk:	volume:4 ; year:2011 ; number:2

Links:	Link aufrufen Link aufrufen Link aufrufen Journal toc

DOI / URN:	10.2991/ijcis.2011.4.2.14

Katalog-ID:	DOAJ031119484

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520			\|a A new method of banknote image retrieval is proposed by using new set of rotated quaternion wavelet filters (RQWF) and standard quaternion wavelet transform (QWT) jointly. The robust and rotationally invariant features are extracted from QWT and RQWF decomposed sub-bands of banknote image. Three different sets of databases are used to demonstrate the effectiveness of the proposed method. The experimental results show that the proposed method improves the recognition rate from 78.79% to 91.22% on (16000 images) database D1, form 74.08% to 94.62% on (20000 images) database D2 and from 76.44% to 88.78% on (10000 images) database D3. The proposed method can also obtain a reasonable level of computational complexity.
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spelling	10.2991/ijcis.2011.4.2.14 doi (DE-627)DOAJ031119484 (DE-599)DOAJ6935befe5fa741a5b04d39417846f9cf DE-627 ger DE-627 rakwb eng QA75.5-76.95 Shan Gai verfasserin aut Banknote Image Retrieval Using Rotated QuaternionWavelet Filters 2011 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier A new method of banknote image retrieval is proposed by using new set of rotated quaternion wavelet filters (RQWF) and standard quaternion wavelet transform (QWT) jointly. The robust and rotationally invariant features are extracted from QWT and RQWF decomposed sub-bands of banknote image. Three different sets of databases are used to demonstrate the effectiveness of the proposed method. The experimental results show that the proposed method improves the recognition rate from 78.79% to 91.22% on (16000 images) database D1, form 74.08% to 94.62% on (20000 images) database D2 and from 76.44% to 88.78% on (10000 images) database D3. The proposed method can also obtain a reasonable level of computational complexity. discrete wavelet transform (DWT) complex wavelet transform (CWT) quaternion wavelet transform (QWT) rotated quaternion wavelet filters (RQWF) feature extraction support vector machine (SVM). Electronic computers. Computer science Jiafeng Liu verfasserin aut Xianglong Tang verfasserin aut In International Journal of Computational Intelligence Systems Springer, 2017 4(2011), 2 (DE-627)777781514 (DE-600)2754752-8 18756883 nnns volume:4 year:2011 number:2 https://doi.org/10.2991/ijcis.2011.4.2.14 kostenfrei https://doaj.org/article/6935befe5fa741a5b04d39417846f9cf kostenfrei https://www.atlantis-press.com/article/2147.pdf kostenfrei https://doaj.org/toc/1875-6883 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 4 2011 2
allfields_unstemmed	10.2991/ijcis.2011.4.2.14 doi (DE-627)DOAJ031119484 (DE-599)DOAJ6935befe5fa741a5b04d39417846f9cf DE-627 ger DE-627 rakwb eng QA75.5-76.95 Shan Gai verfasserin aut Banknote Image Retrieval Using Rotated QuaternionWavelet Filters 2011 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier A new method of banknote image retrieval is proposed by using new set of rotated quaternion wavelet filters (RQWF) and standard quaternion wavelet transform (QWT) jointly. The robust and rotationally invariant features are extracted from QWT and RQWF decomposed sub-bands of banknote image. Three different sets of databases are used to demonstrate the effectiveness of the proposed method. The experimental results show that the proposed method improves the recognition rate from 78.79% to 91.22% on (16000 images) database D1, form 74.08% to 94.62% on (20000 images) database D2 and from 76.44% to 88.78% on (10000 images) database D3. The proposed method can also obtain a reasonable level of computational complexity. discrete wavelet transform (DWT) complex wavelet transform (CWT) quaternion wavelet transform (QWT) rotated quaternion wavelet filters (RQWF) feature extraction support vector machine (SVM). Electronic computers. Computer science Jiafeng Liu verfasserin aut Xianglong Tang verfasserin aut In International Journal of Computational Intelligence Systems Springer, 2017 4(2011), 2 (DE-627)777781514 (DE-600)2754752-8 18756883 nnns volume:4 year:2011 number:2 https://doi.org/10.2991/ijcis.2011.4.2.14 kostenfrei https://doaj.org/article/6935befe5fa741a5b04d39417846f9cf kostenfrei https://www.atlantis-press.com/article/2147.pdf kostenfrei https://doaj.org/toc/1875-6883 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 4 2011 2
allfieldsGer	10.2991/ijcis.2011.4.2.14 doi (DE-627)DOAJ031119484 (DE-599)DOAJ6935befe5fa741a5b04d39417846f9cf DE-627 ger DE-627 rakwb eng QA75.5-76.95 Shan Gai verfasserin aut Banknote Image Retrieval Using Rotated QuaternionWavelet Filters 2011 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier A new method of banknote image retrieval is proposed by using new set of rotated quaternion wavelet filters (RQWF) and standard quaternion wavelet transform (QWT) jointly. The robust and rotationally invariant features are extracted from QWT and RQWF decomposed sub-bands of banknote image. Three different sets of databases are used to demonstrate the effectiveness of the proposed method. The experimental results show that the proposed method improves the recognition rate from 78.79% to 91.22% on (16000 images) database D1, form 74.08% to 94.62% on (20000 images) database D2 and from 76.44% to 88.78% on (10000 images) database D3. The proposed method can also obtain a reasonable level of computational complexity. discrete wavelet transform (DWT) complex wavelet transform (CWT) quaternion wavelet transform (QWT) rotated quaternion wavelet filters (RQWF) feature extraction support vector machine (SVM). Electronic computers. Computer science Jiafeng Liu verfasserin aut Xianglong Tang verfasserin aut In International Journal of Computational Intelligence Systems Springer, 2017 4(2011), 2 (DE-627)777781514 (DE-600)2754752-8 18756883 nnns volume:4 year:2011 number:2 https://doi.org/10.2991/ijcis.2011.4.2.14 kostenfrei https://doaj.org/article/6935befe5fa741a5b04d39417846f9cf kostenfrei https://www.atlantis-press.com/article/2147.pdf kostenfrei https://doaj.org/toc/1875-6883 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 4 2011 2
allfieldsSound	10.2991/ijcis.2011.4.2.14 doi (DE-627)DOAJ031119484 (DE-599)DOAJ6935befe5fa741a5b04d39417846f9cf DE-627 ger DE-627 rakwb eng QA75.5-76.95 Shan Gai verfasserin aut Banknote Image Retrieval Using Rotated QuaternionWavelet Filters 2011 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier A new method of banknote image retrieval is proposed by using new set of rotated quaternion wavelet filters (RQWF) and standard quaternion wavelet transform (QWT) jointly. The robust and rotationally invariant features are extracted from QWT and RQWF decomposed sub-bands of banknote image. Three different sets of databases are used to demonstrate the effectiveness of the proposed method. The experimental results show that the proposed method improves the recognition rate from 78.79% to 91.22% on (16000 images) database D1, form 74.08% to 94.62% on (20000 images) database D2 and from 76.44% to 88.78% on (10000 images) database D3. The proposed method can also obtain a reasonable level of computational complexity. discrete wavelet transform (DWT) complex wavelet transform (CWT) quaternion wavelet transform (QWT) rotated quaternion wavelet filters (RQWF) feature extraction support vector machine (SVM). Electronic computers. Computer science Jiafeng Liu verfasserin aut Xianglong Tang verfasserin aut In International Journal of Computational Intelligence Systems Springer, 2017 4(2011), 2 (DE-627)777781514 (DE-600)2754752-8 18756883 nnns volume:4 year:2011 number:2 https://doi.org/10.2991/ijcis.2011.4.2.14 kostenfrei https://doaj.org/article/6935befe5fa741a5b04d39417846f9cf kostenfrei https://www.atlantis-press.com/article/2147.pdf kostenfrei https://doaj.org/toc/1875-6883 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 4 2011 2
language	English
source	In International Journal of Computational Intelligence Systems 4(2011), 2 volume:4 year:2011 number:2
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institution	findex.gbv.de
topic_facet	discrete wavelet transform (DWT) complex wavelet transform (CWT) quaternion wavelet transform (QWT) rotated quaternion wavelet filters (RQWF) feature extraction support vector machine (SVM). Electronic computers. Computer science
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callnumber-first	Q - Science
author	Shan Gai
spellingShingle	Shan Gai misc QA75.5-76.95 misc discrete wavelet transform (DWT) misc complex wavelet transform (CWT) misc quaternion wavelet transform (QWT) misc rotated quaternion wavelet filters (RQWF) misc feature extraction misc support vector machine (SVM). misc Electronic computers. Computer science Banknote Image Retrieval Using Rotated QuaternionWavelet Filters
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topic_title	QA75.5-76.95 Banknote Image Retrieval Using Rotated QuaternionWavelet Filters discrete wavelet transform (DWT) complex wavelet transform (CWT) quaternion wavelet transform (QWT) rotated quaternion wavelet filters (RQWF) feature extraction support vector machine (SVM)
topic	misc QA75.5-76.95 misc discrete wavelet transform (DWT) misc complex wavelet transform (CWT) misc quaternion wavelet transform (QWT) misc rotated quaternion wavelet filters (RQWF) misc feature extraction misc support vector machine (SVM). misc Electronic computers. Computer science
topic_unstemmed	misc QA75.5-76.95 misc discrete wavelet transform (DWT) misc complex wavelet transform (CWT) misc quaternion wavelet transform (QWT) misc rotated quaternion wavelet filters (RQWF) misc feature extraction misc support vector machine (SVM). misc Electronic computers. Computer science
topic_browse	misc QA75.5-76.95 misc discrete wavelet transform (DWT) misc complex wavelet transform (CWT) misc quaternion wavelet transform (QWT) misc rotated quaternion wavelet filters (RQWF) misc feature extraction misc support vector machine (SVM). misc Electronic computers. Computer science
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title	Banknote Image Retrieval Using Rotated QuaternionWavelet Filters
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title_full	Banknote Image Retrieval Using Rotated QuaternionWavelet Filters
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title_sort	banknote image retrieval using rotated quaternionwavelet filters
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title_auth	Banknote Image Retrieval Using Rotated QuaternionWavelet Filters
abstract	A new method of banknote image retrieval is proposed by using new set of rotated quaternion wavelet filters (RQWF) and standard quaternion wavelet transform (QWT) jointly. The robust and rotationally invariant features are extracted from QWT and RQWF decomposed sub-bands of banknote image. Three different sets of databases are used to demonstrate the effectiveness of the proposed method. The experimental results show that the proposed method improves the recognition rate from 78.79% to 91.22% on (16000 images) database D1, form 74.08% to 94.62% on (20000 images) database D2 and from 76.44% to 88.78% on (10000 images) database D3. The proposed method can also obtain a reasonable level of computational complexity.
abstractGer	A new method of banknote image retrieval is proposed by using new set of rotated quaternion wavelet filters (RQWF) and standard quaternion wavelet transform (QWT) jointly. The robust and rotationally invariant features are extracted from QWT and RQWF decomposed sub-bands of banknote image. Three different sets of databases are used to demonstrate the effectiveness of the proposed method. The experimental results show that the proposed method improves the recognition rate from 78.79% to 91.22% on (16000 images) database D1, form 74.08% to 94.62% on (20000 images) database D2 and from 76.44% to 88.78% on (10000 images) database D3. The proposed method can also obtain a reasonable level of computational complexity.
abstract_unstemmed	A new method of banknote image retrieval is proposed by using new set of rotated quaternion wavelet filters (RQWF) and standard quaternion wavelet transform (QWT) jointly. The robust and rotationally invariant features are extracted from QWT and RQWF decomposed sub-bands of banknote image. Three different sets of databases are used to demonstrate the effectiveness of the proposed method. The experimental results show that the proposed method improves the recognition rate from 78.79% to 91.22% on (16000 images) database D1, form 74.08% to 94.62% on (20000 images) database D2 and from 76.44% to 88.78% on (10000 images) database D3. The proposed method can also obtain a reasonable level of computational complexity.
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title_short	Banknote Image Retrieval Using Rotated QuaternionWavelet Filters
url	https://doi.org/10.2991/ijcis.2011.4.2.14 https://doaj.org/article/6935befe5fa741a5b04d39417846f9cf https://www.atlantis-press.com/article/2147.pdf https://doaj.org/toc/1875-6883
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up_date	2024-07-03T18:51:32.025Z
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