2D2LPI : Two Directional Two Dimensional Locality Preserving Indexing
In this paper, a new method of representing images called two directional two dimensional locality preserving indexing called 2D2LPI is presented. It is an extension of the two dimensional locality preserving indexing (2DLPI) method. The authors argue that the recently proposed 2DLPI reduces the dim...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Manjunath, S [verfasserIn] Guru, D S [verfasserIn] Nagasundara, K B [verfasserIn] Suraj, M G [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2013 |
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| Umfang: |
1 Online-Ressource |
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| Übergeordnetes Werk: |
Enthalten in: International journal of computer vision and image processing - Hershey, Pa : IGI Global, 2011, 3(2013), 2, Seite 17-31 |
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| Übergeordnetes Werk: |
volume:3 ; year:2013 ; number:2 ; pages:17-31 |
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| DOI / URN: |
10.4018/ijcvip.2013040102 |
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NLEJ251794490 |
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| 520 | |a In this paper, a new method of representing images called two directional two dimensional locality preserving indexing called 2D2LPI is presented. It is an extension of the two dimensional locality preserving indexing (2DLPI) method. The authors argue that the recently proposed 2DLPI reduces the dimensions of images in row direction and we propose an alternate way of reducing the dimension in column direction. Later the authors propose a method to reduce the size of an image both in row and column directions. To corroborate the efficacy of the proposed two directional two dimensional approach the authors design a model for person identification based on single instance of finger knuckle print and subsequently the authors propose a feature level fusion of multi-instance finger knuckle print for person identification. Also to study the suitability of the proposed approach on a different domain, a study on video summarization is also presented in this paper. The results of the proposed method are compared with that of the state of the art techniques such as 2D2PCA, 2D2LPP and it is found that the proposed 2D2LPI model is more competitive in terms of accuracy | ||
| 653 | |a Feature Level Fusion |a Locality Preserving Indexing |a Multi-Instance Finger Knuckle Print Recognition |a Two Dimensional Locality Preserving Indexing (2DLPI) |a Two-Directional Two-Dimensional Locality Preserving Indexing (2D2LPI) |a Video Summarization | ||
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| 700 | 1 | |a Nagasundara, K B |e verfasserin |4 aut | |
| 700 | 1 | |a Suraj, M G |e verfasserin |4 aut | |
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10.4018/ijcvip.2013040102 doi (DE-627)NLEJ251794490 (VZGNL)10.4018/ijcvip.2013040102 DE-627 ger DE-627 rakwb eng Manjunath, S verfasserin aut 2D2LPI Two Directional Two Dimensional Locality Preserving Indexing 2013 1 Online-Ressource Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier In this paper, a new method of representing images called two directional two dimensional locality preserving indexing called 2D2LPI is presented. It is an extension of the two dimensional locality preserving indexing (2DLPI) method. The authors argue that the recently proposed 2DLPI reduces the dimensions of images in row direction and we propose an alternate way of reducing the dimension in column direction. Later the authors propose a method to reduce the size of an image both in row and column directions. To corroborate the efficacy of the proposed two directional two dimensional approach the authors design a model for person identification based on single instance of finger knuckle print and subsequently the authors propose a feature level fusion of multi-instance finger knuckle print for person identification. Also to study the suitability of the proposed approach on a different domain, a study on video summarization is also presented in this paper. The results of the proposed method are compared with that of the state of the art techniques such as 2D2PCA, 2D2LPP and it is found that the proposed 2D2LPI model is more competitive in terms of accuracy Feature Level Fusion Locality Preserving Indexing Multi-Instance Finger Knuckle Print Recognition Two Dimensional Locality Preserving Indexing (2DLPI) Two-Directional Two-Dimensional Locality Preserving Indexing (2D2LPI) Video Summarization Guru, D S verfasserin aut Nagasundara, K B verfasserin aut Suraj, M G verfasserin aut Enthalten in International journal of computer vision and image processing Hershey, Pa : IGI Global, 2011 3(2013), 2, Seite 17-31 Online-Ressource (DE-627)NLEJ244418802 (DE-600)2703057-X 2155-6989 nnns volume:3 year:2013 number:2 pages:17-31 http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/ijcvip.2013040102 X:IGIG Verlag Deutschlandweit zugänglich http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/ijcvip.2013040102&buylink=true Abstract ZDB-1-GIS GBV_NL_ARTICLE AR 3 2013 2 17-31 |
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10.4018/ijcvip.2013040102 doi (DE-627)NLEJ251794490 (VZGNL)10.4018/ijcvip.2013040102 DE-627 ger DE-627 rakwb eng Manjunath, S verfasserin aut 2D2LPI Two Directional Two Dimensional Locality Preserving Indexing 2013 1 Online-Ressource Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier In this paper, a new method of representing images called two directional two dimensional locality preserving indexing called 2D2LPI is presented. It is an extension of the two dimensional locality preserving indexing (2DLPI) method. The authors argue that the recently proposed 2DLPI reduces the dimensions of images in row direction and we propose an alternate way of reducing the dimension in column direction. Later the authors propose a method to reduce the size of an image both in row and column directions. To corroborate the efficacy of the proposed two directional two dimensional approach the authors design a model for person identification based on single instance of finger knuckle print and subsequently the authors propose a feature level fusion of multi-instance finger knuckle print for person identification. Also to study the suitability of the proposed approach on a different domain, a study on video summarization is also presented in this paper. The results of the proposed method are compared with that of the state of the art techniques such as 2D2PCA, 2D2LPP and it is found that the proposed 2D2LPI model is more competitive in terms of accuracy Feature Level Fusion Locality Preserving Indexing Multi-Instance Finger Knuckle Print Recognition Two Dimensional Locality Preserving Indexing (2DLPI) Two-Directional Two-Dimensional Locality Preserving Indexing (2D2LPI) Video Summarization Guru, D S verfasserin aut Nagasundara, K B verfasserin aut Suraj, M G verfasserin aut Enthalten in International journal of computer vision and image processing Hershey, Pa : IGI Global, 2011 3(2013), 2, Seite 17-31 Online-Ressource (DE-627)NLEJ244418802 (DE-600)2703057-X 2155-6989 nnns volume:3 year:2013 number:2 pages:17-31 http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/ijcvip.2013040102 X:IGIG Verlag Deutschlandweit zugänglich http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/ijcvip.2013040102&buylink=true Abstract ZDB-1-GIS GBV_NL_ARTICLE AR 3 2013 2 17-31 |
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10.4018/ijcvip.2013040102 doi (DE-627)NLEJ251794490 (VZGNL)10.4018/ijcvip.2013040102 DE-627 ger DE-627 rakwb eng Manjunath, S verfasserin aut 2D2LPI Two Directional Two Dimensional Locality Preserving Indexing 2013 1 Online-Ressource Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier In this paper, a new method of representing images called two directional two dimensional locality preserving indexing called 2D2LPI is presented. It is an extension of the two dimensional locality preserving indexing (2DLPI) method. The authors argue that the recently proposed 2DLPI reduces the dimensions of images in row direction and we propose an alternate way of reducing the dimension in column direction. Later the authors propose a method to reduce the size of an image both in row and column directions. To corroborate the efficacy of the proposed two directional two dimensional approach the authors design a model for person identification based on single instance of finger knuckle print and subsequently the authors propose a feature level fusion of multi-instance finger knuckle print for person identification. Also to study the suitability of the proposed approach on a different domain, a study on video summarization is also presented in this paper. The results of the proposed method are compared with that of the state of the art techniques such as 2D2PCA, 2D2LPP and it is found that the proposed 2D2LPI model is more competitive in terms of accuracy Feature Level Fusion Locality Preserving Indexing Multi-Instance Finger Knuckle Print Recognition Two Dimensional Locality Preserving Indexing (2DLPI) Two-Directional Two-Dimensional Locality Preserving Indexing (2D2LPI) Video Summarization Guru, D S verfasserin aut Nagasundara, K B verfasserin aut Suraj, M G verfasserin aut Enthalten in International journal of computer vision and image processing Hershey, Pa : IGI Global, 2011 3(2013), 2, Seite 17-31 Online-Ressource (DE-627)NLEJ244418802 (DE-600)2703057-X 2155-6989 nnns volume:3 year:2013 number:2 pages:17-31 http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/ijcvip.2013040102 X:IGIG Verlag Deutschlandweit zugänglich http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/ijcvip.2013040102&buylink=true Abstract ZDB-1-GIS GBV_NL_ARTICLE AR 3 2013 2 17-31 |
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10.4018/ijcvip.2013040102 doi (DE-627)NLEJ251794490 (VZGNL)10.4018/ijcvip.2013040102 DE-627 ger DE-627 rakwb eng Manjunath, S verfasserin aut 2D2LPI Two Directional Two Dimensional Locality Preserving Indexing 2013 1 Online-Ressource Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier In this paper, a new method of representing images called two directional two dimensional locality preserving indexing called 2D2LPI is presented. It is an extension of the two dimensional locality preserving indexing (2DLPI) method. The authors argue that the recently proposed 2DLPI reduces the dimensions of images in row direction and we propose an alternate way of reducing the dimension in column direction. Later the authors propose a method to reduce the size of an image both in row and column directions. To corroborate the efficacy of the proposed two directional two dimensional approach the authors design a model for person identification based on single instance of finger knuckle print and subsequently the authors propose a feature level fusion of multi-instance finger knuckle print for person identification. Also to study the suitability of the proposed approach on a different domain, a study on video summarization is also presented in this paper. The results of the proposed method are compared with that of the state of the art techniques such as 2D2PCA, 2D2LPP and it is found that the proposed 2D2LPI model is more competitive in terms of accuracy Feature Level Fusion Locality Preserving Indexing Multi-Instance Finger Knuckle Print Recognition Two Dimensional Locality Preserving Indexing (2DLPI) Two-Directional Two-Dimensional Locality Preserving Indexing (2D2LPI) Video Summarization Guru, D S verfasserin aut Nagasundara, K B verfasserin aut Suraj, M G verfasserin aut Enthalten in International journal of computer vision and image processing Hershey, Pa : IGI Global, 2011 3(2013), 2, Seite 17-31 Online-Ressource (DE-627)NLEJ244418802 (DE-600)2703057-X 2155-6989 nnns volume:3 year:2013 number:2 pages:17-31 http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/ijcvip.2013040102 X:IGIG Verlag Deutschlandweit zugänglich http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/ijcvip.2013040102&buylink=true Abstract ZDB-1-GIS GBV_NL_ARTICLE AR 3 2013 2 17-31 |
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10.4018/ijcvip.2013040102 doi (DE-627)NLEJ251794490 (VZGNL)10.4018/ijcvip.2013040102 DE-627 ger DE-627 rakwb eng Manjunath, S verfasserin aut 2D2LPI Two Directional Two Dimensional Locality Preserving Indexing 2013 1 Online-Ressource Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier In this paper, a new method of representing images called two directional two dimensional locality preserving indexing called 2D2LPI is presented. It is an extension of the two dimensional locality preserving indexing (2DLPI) method. The authors argue that the recently proposed 2DLPI reduces the dimensions of images in row direction and we propose an alternate way of reducing the dimension in column direction. Later the authors propose a method to reduce the size of an image both in row and column directions. To corroborate the efficacy of the proposed two directional two dimensional approach the authors design a model for person identification based on single instance of finger knuckle print and subsequently the authors propose a feature level fusion of multi-instance finger knuckle print for person identification. Also to study the suitability of the proposed approach on a different domain, a study on video summarization is also presented in this paper. The results of the proposed method are compared with that of the state of the art techniques such as 2D2PCA, 2D2LPP and it is found that the proposed 2D2LPI model is more competitive in terms of accuracy Feature Level Fusion Locality Preserving Indexing Multi-Instance Finger Knuckle Print Recognition Two Dimensional Locality Preserving Indexing (2DLPI) Two-Directional Two-Dimensional Locality Preserving Indexing (2D2LPI) Video Summarization Guru, D S verfasserin aut Nagasundara, K B verfasserin aut Suraj, M G verfasserin aut Enthalten in International journal of computer vision and image processing Hershey, Pa : IGI Global, 2011 3(2013), 2, Seite 17-31 Online-Ressource (DE-627)NLEJ244418802 (DE-600)2703057-X 2155-6989 nnns volume:3 year:2013 number:2 pages:17-31 http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/ijcvip.2013040102 X:IGIG Verlag Deutschlandweit zugänglich http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/ijcvip.2013040102&buylink=true Abstract ZDB-1-GIS GBV_NL_ARTICLE AR 3 2013 2 17-31 |
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2D2LPI Two Directional Two Dimensional Locality Preserving Indexing |
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In this paper, a new method of representing images called two directional two dimensional locality preserving indexing called 2D2LPI is presented. It is an extension of the two dimensional locality preserving indexing (2DLPI) method. The authors argue that the recently proposed 2DLPI reduces the dimensions of images in row direction and we propose an alternate way of reducing the dimension in column direction. Later the authors propose a method to reduce the size of an image both in row and column directions. To corroborate the efficacy of the proposed two directional two dimensional approach the authors design a model for person identification based on single instance of finger knuckle print and subsequently the authors propose a feature level fusion of multi-instance finger knuckle print for person identification. Also to study the suitability of the proposed approach on a different domain, a study on video summarization is also presented in this paper. The results of the proposed method are compared with that of the state of the art techniques such as 2D2PCA, 2D2LPP and it is found that the proposed 2D2LPI model is more competitive in terms of accuracy |
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In this paper, a new method of representing images called two directional two dimensional locality preserving indexing called 2D2LPI is presented. It is an extension of the two dimensional locality preserving indexing (2DLPI) method. The authors argue that the recently proposed 2DLPI reduces the dimensions of images in row direction and we propose an alternate way of reducing the dimension in column direction. Later the authors propose a method to reduce the size of an image both in row and column directions. To corroborate the efficacy of the proposed two directional two dimensional approach the authors design a model for person identification based on single instance of finger knuckle print and subsequently the authors propose a feature level fusion of multi-instance finger knuckle print for person identification. Also to study the suitability of the proposed approach on a different domain, a study on video summarization is also presented in this paper. The results of the proposed method are compared with that of the state of the art techniques such as 2D2PCA, 2D2LPP and it is found that the proposed 2D2LPI model is more competitive in terms of accuracy |
| abstract_unstemmed |
In this paper, a new method of representing images called two directional two dimensional locality preserving indexing called 2D2LPI is presented. It is an extension of the two dimensional locality preserving indexing (2DLPI) method. The authors argue that the recently proposed 2DLPI reduces the dimensions of images in row direction and we propose an alternate way of reducing the dimension in column direction. Later the authors propose a method to reduce the size of an image both in row and column directions. To corroborate the efficacy of the proposed two directional two dimensional approach the authors design a model for person identification based on single instance of finger knuckle print and subsequently the authors propose a feature level fusion of multi-instance finger knuckle print for person identification. Also to study the suitability of the proposed approach on a different domain, a study on video summarization is also presented in this paper. The results of the proposed method are compared with that of the state of the art techniques such as 2D2PCA, 2D2LPP and it is found that the proposed 2D2LPI model is more competitive in terms of accuracy |
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Guru, D S Nagasundara, K B Suraj, M G |
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