A new 2D shape retrieval scheme based on phase congruency and histogram of oriented gradients
Abstract Shape matching and retrieval is a challenging issue in computer vision owing to the complications in realizing highly accurate descriptors. Herein, a novel shape characterization, representation scheme is presented by blending phase congruency (PC) with histogram of oriented gradients (HOG)...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Govindaraj, P. [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2019 |
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| Schlagwörter: |
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| Anmerkung: |
© Springer-Verlag London Ltd., part of Springer Nature 2019 |
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| Übergeordnetes Werk: |
Enthalten in: Signal, image and video processing - London [u.a.] : Springer, 2007, 13(2019), 4 vom: 02. Jan., Seite 771-778 |
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| Übergeordnetes Werk: |
volume:13 ; year:2019 ; number:4 ; day:02 ; month:01 ; pages:771-778 |
| Links: |
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| DOI / URN: |
10.1007/s11760-018-1407-5 |
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SPR022278133 |
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| 245 | 1 | 2 | |a A new 2D shape retrieval scheme based on phase congruency and histogram of oriented gradients |
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| 520 | |a Abstract Shape matching and retrieval is a challenging issue in computer vision owing to the complications in realizing highly accurate descriptors. Herein, a novel shape characterization, representation scheme is presented by blending phase congruency (PC) with histogram of oriented gradients (HOG), labelled as PC-HOG. Firstly, PC is applied on the shapes to obtain contour points that is then operated by HOG to formulate the feature vector. The resulting descriptor is evaluated on shape datasets like MPEG-7 CE shape-1 part B, TARI-1000 and Kimia’s 99. Relatively consistent Bull’s Eye Retrieval rate of 90% was achieved by the proposed descriptor across the diverse datasets. Also, noise analysis of the proposed descriptor in diverse datasets is performed to signify the scheme’s robustness against noise. Furthermore, the inherent nature of PC-HOG makes it to be invariant to different affine transformations. | ||
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| 650 | 4 | |a Shape retrieval |7 (dpeaa)DE-He213 | |
| 700 | 1 | |a Sudhakar, M. S. |4 aut | |
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10.1007/s11760-018-1407-5 doi (DE-627)SPR022278133 (SPR)s11760-018-1407-5-e DE-627 ger DE-627 rakwb eng Govindaraj, P. verfasserin (orcid)0000-0003-0788-8914 aut A new 2D shape retrieval scheme based on phase congruency and histogram of oriented gradients 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Springer-Verlag London Ltd., part of Springer Nature 2019 Abstract Shape matching and retrieval is a challenging issue in computer vision owing to the complications in realizing highly accurate descriptors. Herein, a novel shape characterization, representation scheme is presented by blending phase congruency (PC) with histogram of oriented gradients (HOG), labelled as PC-HOG. Firstly, PC is applied on the shapes to obtain contour points that is then operated by HOG to formulate the feature vector. The resulting descriptor is evaluated on shape datasets like MPEG-7 CE shape-1 part B, TARI-1000 and Kimia’s 99. Relatively consistent Bull’s Eye Retrieval rate of 90% was achieved by the proposed descriptor across the diverse datasets. Also, noise analysis of the proposed descriptor in diverse datasets is performed to signify the scheme’s robustness against noise. Furthermore, the inherent nature of PC-HOG makes it to be invariant to different affine transformations. Bulls Eye Score (dpeaa)DE-He213 Histogram of oriented gradients (dpeaa)DE-He213 Phase congruency (dpeaa)DE-He213 Shape retrieval (dpeaa)DE-He213 Sudhakar, M. S. aut Enthalten in Signal, image and video processing London [u.a.] : Springer, 2007 13(2019), 4 vom: 02. Jan., Seite 771-778 (DE-627)546899102 (DE-600)2391619-9 1863-1711 nnns volume:13 year:2019 number:4 day:02 month:01 pages:771-778 https://dx.doi.org/10.1007/s11760-018-1407-5 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 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_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 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_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 13 2019 4 02 01 771-778 |
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10.1007/s11760-018-1407-5 doi (DE-627)SPR022278133 (SPR)s11760-018-1407-5-e DE-627 ger DE-627 rakwb eng Govindaraj, P. verfasserin (orcid)0000-0003-0788-8914 aut A new 2D shape retrieval scheme based on phase congruency and histogram of oriented gradients 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Springer-Verlag London Ltd., part of Springer Nature 2019 Abstract Shape matching and retrieval is a challenging issue in computer vision owing to the complications in realizing highly accurate descriptors. Herein, a novel shape characterization, representation scheme is presented by blending phase congruency (PC) with histogram of oriented gradients (HOG), labelled as PC-HOG. Firstly, PC is applied on the shapes to obtain contour points that is then operated by HOG to formulate the feature vector. The resulting descriptor is evaluated on shape datasets like MPEG-7 CE shape-1 part B, TARI-1000 and Kimia’s 99. Relatively consistent Bull’s Eye Retrieval rate of 90% was achieved by the proposed descriptor across the diverse datasets. Also, noise analysis of the proposed descriptor in diverse datasets is performed to signify the scheme’s robustness against noise. Furthermore, the inherent nature of PC-HOG makes it to be invariant to different affine transformations. Bulls Eye Score (dpeaa)DE-He213 Histogram of oriented gradients (dpeaa)DE-He213 Phase congruency (dpeaa)DE-He213 Shape retrieval (dpeaa)DE-He213 Sudhakar, M. S. aut Enthalten in Signal, image and video processing London [u.a.] : Springer, 2007 13(2019), 4 vom: 02. Jan., Seite 771-778 (DE-627)546899102 (DE-600)2391619-9 1863-1711 nnns volume:13 year:2019 number:4 day:02 month:01 pages:771-778 https://dx.doi.org/10.1007/s11760-018-1407-5 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 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_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 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_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 13 2019 4 02 01 771-778 |
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10.1007/s11760-018-1407-5 doi (DE-627)SPR022278133 (SPR)s11760-018-1407-5-e DE-627 ger DE-627 rakwb eng Govindaraj, P. verfasserin (orcid)0000-0003-0788-8914 aut A new 2D shape retrieval scheme based on phase congruency and histogram of oriented gradients 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Springer-Verlag London Ltd., part of Springer Nature 2019 Abstract Shape matching and retrieval is a challenging issue in computer vision owing to the complications in realizing highly accurate descriptors. Herein, a novel shape characterization, representation scheme is presented by blending phase congruency (PC) with histogram of oriented gradients (HOG), labelled as PC-HOG. Firstly, PC is applied on the shapes to obtain contour points that is then operated by HOG to formulate the feature vector. The resulting descriptor is evaluated on shape datasets like MPEG-7 CE shape-1 part B, TARI-1000 and Kimia’s 99. Relatively consistent Bull’s Eye Retrieval rate of 90% was achieved by the proposed descriptor across the diverse datasets. Also, noise analysis of the proposed descriptor in diverse datasets is performed to signify the scheme’s robustness against noise. Furthermore, the inherent nature of PC-HOG makes it to be invariant to different affine transformations. Bulls Eye Score (dpeaa)DE-He213 Histogram of oriented gradients (dpeaa)DE-He213 Phase congruency (dpeaa)DE-He213 Shape retrieval (dpeaa)DE-He213 Sudhakar, M. S. aut Enthalten in Signal, image and video processing London [u.a.] : Springer, 2007 13(2019), 4 vom: 02. Jan., Seite 771-778 (DE-627)546899102 (DE-600)2391619-9 1863-1711 nnns volume:13 year:2019 number:4 day:02 month:01 pages:771-778 https://dx.doi.org/10.1007/s11760-018-1407-5 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 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_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 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_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 13 2019 4 02 01 771-778 |
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10.1007/s11760-018-1407-5 doi (DE-627)SPR022278133 (SPR)s11760-018-1407-5-e DE-627 ger DE-627 rakwb eng Govindaraj, P. verfasserin (orcid)0000-0003-0788-8914 aut A new 2D shape retrieval scheme based on phase congruency and histogram of oriented gradients 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Springer-Verlag London Ltd., part of Springer Nature 2019 Abstract Shape matching and retrieval is a challenging issue in computer vision owing to the complications in realizing highly accurate descriptors. Herein, a novel shape characterization, representation scheme is presented by blending phase congruency (PC) with histogram of oriented gradients (HOG), labelled as PC-HOG. Firstly, PC is applied on the shapes to obtain contour points that is then operated by HOG to formulate the feature vector. The resulting descriptor is evaluated on shape datasets like MPEG-7 CE shape-1 part B, TARI-1000 and Kimia’s 99. Relatively consistent Bull’s Eye Retrieval rate of 90% was achieved by the proposed descriptor across the diverse datasets. Also, noise analysis of the proposed descriptor in diverse datasets is performed to signify the scheme’s robustness against noise. Furthermore, the inherent nature of PC-HOG makes it to be invariant to different affine transformations. Bulls Eye Score (dpeaa)DE-He213 Histogram of oriented gradients (dpeaa)DE-He213 Phase congruency (dpeaa)DE-He213 Shape retrieval (dpeaa)DE-He213 Sudhakar, M. S. aut Enthalten in Signal, image and video processing London [u.a.] : Springer, 2007 13(2019), 4 vom: 02. Jan., Seite 771-778 (DE-627)546899102 (DE-600)2391619-9 1863-1711 nnns volume:13 year:2019 number:4 day:02 month:01 pages:771-778 https://dx.doi.org/10.1007/s11760-018-1407-5 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 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_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 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_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 13 2019 4 02 01 771-778 |
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Govindaraj, P. misc Bulls Eye Score misc Histogram of oriented gradients misc Phase congruency misc Shape retrieval A new 2D shape retrieval scheme based on phase congruency and histogram of oriented gradients |
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A new 2D shape retrieval scheme based on phase congruency and histogram of oriented gradients Bulls Eye Score (dpeaa)DE-He213 Histogram of oriented gradients (dpeaa)DE-He213 Phase congruency (dpeaa)DE-He213 Shape retrieval (dpeaa)DE-He213 |
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new 2d shape retrieval scheme based on phase congruency and histogram of oriented gradients |
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A new 2D shape retrieval scheme based on phase congruency and histogram of oriented gradients |
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Abstract Shape matching and retrieval is a challenging issue in computer vision owing to the complications in realizing highly accurate descriptors. Herein, a novel shape characterization, representation scheme is presented by blending phase congruency (PC) with histogram of oriented gradients (HOG), labelled as PC-HOG. Firstly, PC is applied on the shapes to obtain contour points that is then operated by HOG to formulate the feature vector. The resulting descriptor is evaluated on shape datasets like MPEG-7 CE shape-1 part B, TARI-1000 and Kimia’s 99. Relatively consistent Bull’s Eye Retrieval rate of 90% was achieved by the proposed descriptor across the diverse datasets. Also, noise analysis of the proposed descriptor in diverse datasets is performed to signify the scheme’s robustness against noise. Furthermore, the inherent nature of PC-HOG makes it to be invariant to different affine transformations. © Springer-Verlag London Ltd., part of Springer Nature 2019 |
| abstractGer |
Abstract Shape matching and retrieval is a challenging issue in computer vision owing to the complications in realizing highly accurate descriptors. Herein, a novel shape characterization, representation scheme is presented by blending phase congruency (PC) with histogram of oriented gradients (HOG), labelled as PC-HOG. Firstly, PC is applied on the shapes to obtain contour points that is then operated by HOG to formulate the feature vector. The resulting descriptor is evaluated on shape datasets like MPEG-7 CE shape-1 part B, TARI-1000 and Kimia’s 99. Relatively consistent Bull’s Eye Retrieval rate of 90% was achieved by the proposed descriptor across the diverse datasets. Also, noise analysis of the proposed descriptor in diverse datasets is performed to signify the scheme’s robustness against noise. Furthermore, the inherent nature of PC-HOG makes it to be invariant to different affine transformations. © Springer-Verlag London Ltd., part of Springer Nature 2019 |
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Abstract Shape matching and retrieval is a challenging issue in computer vision owing to the complications in realizing highly accurate descriptors. Herein, a novel shape characterization, representation scheme is presented by blending phase congruency (PC) with histogram of oriented gradients (HOG), labelled as PC-HOG. Firstly, PC is applied on the shapes to obtain contour points that is then operated by HOG to formulate the feature vector. The resulting descriptor is evaluated on shape datasets like MPEG-7 CE shape-1 part B, TARI-1000 and Kimia’s 99. Relatively consistent Bull’s Eye Retrieval rate of 90% was achieved by the proposed descriptor across the diverse datasets. Also, noise analysis of the proposed descriptor in diverse datasets is performed to signify the scheme’s robustness against noise. Furthermore, the inherent nature of PC-HOG makes it to be invariant to different affine transformations. © Springer-Verlag London Ltd., part of Springer Nature 2019 |
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<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000caa a22002652 4500</leader><controlfield tag="001">SPR022278133</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20230330073555.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">201006s2019 xx |||||o 00| ||eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1007/s11760-018-1407-5</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)SPR022278133</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(SPR)s11760-018-1407-5-e</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Govindaraj, P.</subfield><subfield code="e">verfasserin</subfield><subfield code="0">(orcid)0000-0003-0788-8914</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="2"><subfield code="a">A new 2D shape retrieval scheme based on phase congruency and histogram of oriented gradients</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2019</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">Text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">Computermedien</subfield><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Online-Ressource</subfield><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="500" ind1=" " ind2=" "><subfield code="a">© Springer-Verlag London Ltd., part of Springer Nature 2019</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Abstract Shape matching and retrieval is a challenging issue in computer vision owing to the complications in realizing highly accurate descriptors. Herein, a novel shape characterization, representation scheme is presented by blending phase congruency (PC) with histogram of oriented gradients (HOG), labelled as PC-HOG. Firstly, PC is applied on the shapes to obtain contour points that is then operated by HOG to formulate the feature vector. The resulting descriptor is evaluated on shape datasets like MPEG-7 CE shape-1 part B, TARI-1000 and Kimia’s 99. Relatively consistent Bull’s Eye Retrieval rate of 90% was achieved by the proposed descriptor across the diverse datasets. Also, noise analysis of the proposed descriptor in diverse datasets is performed to signify the scheme’s robustness against noise. 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