Evaluation of the tepal colour of Begonia x tuberhybrida Voss. for DUS testing using image analysis
Abstract In the framework of variety testing, evaluation of the flower of Begonia xtuberhybrida Voss. is done by experts. The colours of the flowers are compared with the RHS colour chart. For each flower colour a code is given. This method has several disadvantages (data cannot be statistically ana...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Lootens, Peter [verfasserIn] Van Waes, Johan [verfasserIn] Carlier, Lucien [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2006 |
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| Schlagwörter: |
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| Übergeordnetes Werk: |
Enthalten in: Euphytica - Dordrecht [u.a.] : Springer Science + Business Media B.V., 1952, 155(2006), 1-2 vom: 21. Dez., Seite 135-142 |
|---|---|
| Übergeordnetes Werk: |
volume:155 ; year:2006 ; number:1-2 ; day:21 ; month:12 ; pages:135-142 |
| Links: |
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| DOI / URN: |
10.1007/s10681-006-9315-0 |
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| Katalog-ID: |
SPR012406074 |
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| 100 | 1 | |a Lootens, Peter |e verfasserin |4 aut | |
| 245 | 1 | 0 | |a Evaluation of the tepal colour of Begonia x tuberhybrida Voss. for DUS testing using image analysis |
| 264 | 1 | |c 2006 | |
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| 520 | |a Abstract In the framework of variety testing, evaluation of the flower of Begonia xtuberhybrida Voss. is done by experts. The colours of the flowers are compared with the RHS colour chart. For each flower colour a code is given. This method has several disadvantages (data cannot be statistically analyzed with standard ANOVA techniques, bias by the expert is possible, difficult measurement depending on the light environment, ...) that can be overcome with image analysis. In this study several parameters were tested to distinguish the different varieties. Varieties were split in different colour groups (white, red and yellow–orange) and parameters were analyzed. Parameters based on the green colour plain of the RGB colour space resulted in the largest discriminating power. Parameters based on the HSV colour space performed less well. | ||
| 650 | 4 | |a Voss. |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Flower colour |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Image analysis |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Image processing |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Machine vision |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a RHS colour chart |7 (dpeaa)DE-He213 | |
| 700 | 1 | |a Van Waes, Johan |e verfasserin |4 aut | |
| 700 | 1 | |a Carlier, Lucien |e verfasserin |4 aut | |
| 773 | 0 | 8 | |i Enthalten in |t Euphytica |d Dordrecht [u.a.] : Springer Science + Business Media B.V., 1952 |g 155(2006), 1-2 vom: 21. Dez., Seite 135-142 |w (DE-627)312840098 |w (DE-600)2012322-X |x 1573-5060 |7 nnns |
| 773 | 1 | 8 | |g volume:155 |g year:2006 |g number:1-2 |g day:21 |g month:12 |g pages:135-142 |
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10.1007/s10681-006-9315-0 doi (DE-627)SPR012406074 (SPR)s10681-006-9315-0-e DE-627 ger DE-627 rakwb eng 630 640 ASE 48.58 bkl Lootens, Peter verfasserin aut Evaluation of the tepal colour of Begonia x tuberhybrida Voss. for DUS testing using image analysis 2006 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract In the framework of variety testing, evaluation of the flower of Begonia xtuberhybrida Voss. is done by experts. The colours of the flowers are compared with the RHS colour chart. For each flower colour a code is given. This method has several disadvantages (data cannot be statistically analyzed with standard ANOVA techniques, bias by the expert is possible, difficult measurement depending on the light environment, ...) that can be overcome with image analysis. In this study several parameters were tested to distinguish the different varieties. Varieties were split in different colour groups (white, red and yellow–orange) and parameters were analyzed. Parameters based on the green colour plain of the RGB colour space resulted in the largest discriminating power. Parameters based on the HSV colour space performed less well. Voss. (dpeaa)DE-He213 Flower colour (dpeaa)DE-He213 Image analysis (dpeaa)DE-He213 Image processing (dpeaa)DE-He213 Machine vision (dpeaa)DE-He213 RHS colour chart (dpeaa)DE-He213 Van Waes, Johan verfasserin aut Carlier, Lucien verfasserin aut Enthalten in Euphytica Dordrecht [u.a.] : Springer Science + Business Media B.V., 1952 155(2006), 1-2 vom: 21. Dez., Seite 135-142 (DE-627)312840098 (DE-600)2012322-X 1573-5060 nnns volume:155 year:2006 number:1-2 day:21 month:12 pages:135-142 https://dx.doi.org/10.1007/s10681-006-9315-0 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_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_206 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_647 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_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 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_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 48.58 ASE AR 155 2006 1-2 21 12 135-142 |
| spelling |
10.1007/s10681-006-9315-0 doi (DE-627)SPR012406074 (SPR)s10681-006-9315-0-e DE-627 ger DE-627 rakwb eng 630 640 ASE 48.58 bkl Lootens, Peter verfasserin aut Evaluation of the tepal colour of Begonia x tuberhybrida Voss. for DUS testing using image analysis 2006 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract In the framework of variety testing, evaluation of the flower of Begonia xtuberhybrida Voss. is done by experts. The colours of the flowers are compared with the RHS colour chart. For each flower colour a code is given. This method has several disadvantages (data cannot be statistically analyzed with standard ANOVA techniques, bias by the expert is possible, difficult measurement depending on the light environment, ...) that can be overcome with image analysis. In this study several parameters were tested to distinguish the different varieties. Varieties were split in different colour groups (white, red and yellow–orange) and parameters were analyzed. Parameters based on the green colour plain of the RGB colour space resulted in the largest discriminating power. Parameters based on the HSV colour space performed less well. Voss. (dpeaa)DE-He213 Flower colour (dpeaa)DE-He213 Image analysis (dpeaa)DE-He213 Image processing (dpeaa)DE-He213 Machine vision (dpeaa)DE-He213 RHS colour chart (dpeaa)DE-He213 Van Waes, Johan verfasserin aut Carlier, Lucien verfasserin aut Enthalten in Euphytica Dordrecht [u.a.] : Springer Science + Business Media B.V., 1952 155(2006), 1-2 vom: 21. Dez., Seite 135-142 (DE-627)312840098 (DE-600)2012322-X 1573-5060 nnns volume:155 year:2006 number:1-2 day:21 month:12 pages:135-142 https://dx.doi.org/10.1007/s10681-006-9315-0 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_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_206 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_647 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_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 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_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 48.58 ASE AR 155 2006 1-2 21 12 135-142 |
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10.1007/s10681-006-9315-0 doi (DE-627)SPR012406074 (SPR)s10681-006-9315-0-e DE-627 ger DE-627 rakwb eng 630 640 ASE 48.58 bkl Lootens, Peter verfasserin aut Evaluation of the tepal colour of Begonia x tuberhybrida Voss. for DUS testing using image analysis 2006 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract In the framework of variety testing, evaluation of the flower of Begonia xtuberhybrida Voss. is done by experts. The colours of the flowers are compared with the RHS colour chart. For each flower colour a code is given. This method has several disadvantages (data cannot be statistically analyzed with standard ANOVA techniques, bias by the expert is possible, difficult measurement depending on the light environment, ...) that can be overcome with image analysis. In this study several parameters were tested to distinguish the different varieties. Varieties were split in different colour groups (white, red and yellow–orange) and parameters were analyzed. Parameters based on the green colour plain of the RGB colour space resulted in the largest discriminating power. Parameters based on the HSV colour space performed less well. Voss. (dpeaa)DE-He213 Flower colour (dpeaa)DE-He213 Image analysis (dpeaa)DE-He213 Image processing (dpeaa)DE-He213 Machine vision (dpeaa)DE-He213 RHS colour chart (dpeaa)DE-He213 Van Waes, Johan verfasserin aut Carlier, Lucien verfasserin aut Enthalten in Euphytica Dordrecht [u.a.] : Springer Science + Business Media B.V., 1952 155(2006), 1-2 vom: 21. Dez., Seite 135-142 (DE-627)312840098 (DE-600)2012322-X 1573-5060 nnns volume:155 year:2006 number:1-2 day:21 month:12 pages:135-142 https://dx.doi.org/10.1007/s10681-006-9315-0 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_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_206 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_647 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_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 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_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 48.58 ASE AR 155 2006 1-2 21 12 135-142 |
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10.1007/s10681-006-9315-0 doi (DE-627)SPR012406074 (SPR)s10681-006-9315-0-e DE-627 ger DE-627 rakwb eng 630 640 ASE 48.58 bkl Lootens, Peter verfasserin aut Evaluation of the tepal colour of Begonia x tuberhybrida Voss. for DUS testing using image analysis 2006 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract In the framework of variety testing, evaluation of the flower of Begonia xtuberhybrida Voss. is done by experts. The colours of the flowers are compared with the RHS colour chart. For each flower colour a code is given. This method has several disadvantages (data cannot be statistically analyzed with standard ANOVA techniques, bias by the expert is possible, difficult measurement depending on the light environment, ...) that can be overcome with image analysis. In this study several parameters were tested to distinguish the different varieties. Varieties were split in different colour groups (white, red and yellow–orange) and parameters were analyzed. Parameters based on the green colour plain of the RGB colour space resulted in the largest discriminating power. Parameters based on the HSV colour space performed less well. Voss. (dpeaa)DE-He213 Flower colour (dpeaa)DE-He213 Image analysis (dpeaa)DE-He213 Image processing (dpeaa)DE-He213 Machine vision (dpeaa)DE-He213 RHS colour chart (dpeaa)DE-He213 Van Waes, Johan verfasserin aut Carlier, Lucien verfasserin aut Enthalten in Euphytica Dordrecht [u.a.] : Springer Science + Business Media B.V., 1952 155(2006), 1-2 vom: 21. Dez., Seite 135-142 (DE-627)312840098 (DE-600)2012322-X 1573-5060 nnns volume:155 year:2006 number:1-2 day:21 month:12 pages:135-142 https://dx.doi.org/10.1007/s10681-006-9315-0 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_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_206 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_647 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_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 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_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 48.58 ASE AR 155 2006 1-2 21 12 135-142 |
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10.1007/s10681-006-9315-0 doi (DE-627)SPR012406074 (SPR)s10681-006-9315-0-e DE-627 ger DE-627 rakwb eng 630 640 ASE 48.58 bkl Lootens, Peter verfasserin aut Evaluation of the tepal colour of Begonia x tuberhybrida Voss. for DUS testing using image analysis 2006 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract In the framework of variety testing, evaluation of the flower of Begonia xtuberhybrida Voss. is done by experts. The colours of the flowers are compared with the RHS colour chart. For each flower colour a code is given. This method has several disadvantages (data cannot be statistically analyzed with standard ANOVA techniques, bias by the expert is possible, difficult measurement depending on the light environment, ...) that can be overcome with image analysis. In this study several parameters were tested to distinguish the different varieties. Varieties were split in different colour groups (white, red and yellow–orange) and parameters were analyzed. Parameters based on the green colour plain of the RGB colour space resulted in the largest discriminating power. Parameters based on the HSV colour space performed less well. Voss. (dpeaa)DE-He213 Flower colour (dpeaa)DE-He213 Image analysis (dpeaa)DE-He213 Image processing (dpeaa)DE-He213 Machine vision (dpeaa)DE-He213 RHS colour chart (dpeaa)DE-He213 Van Waes, Johan verfasserin aut Carlier, Lucien verfasserin aut Enthalten in Euphytica Dordrecht [u.a.] : Springer Science + Business Media B.V., 1952 155(2006), 1-2 vom: 21. Dez., Seite 135-142 (DE-627)312840098 (DE-600)2012322-X 1573-5060 nnns volume:155 year:2006 number:1-2 day:21 month:12 pages:135-142 https://dx.doi.org/10.1007/s10681-006-9315-0 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_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_206 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_647 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_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 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_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 48.58 ASE AR 155 2006 1-2 21 12 135-142 |
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Enthalten in Euphytica 155(2006), 1-2 vom: 21. Dez., Seite 135-142 volume:155 year:2006 number:1-2 day:21 month:12 pages:135-142 |
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Voss. Flower colour Image analysis Image processing Machine vision RHS colour chart |
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Lootens, Peter @@aut@@ Van Waes, Johan @@aut@@ Carlier, Lucien @@aut@@ |
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Lootens, Peter |
| spellingShingle |
Lootens, Peter ddc 630 bkl 48.58 misc Voss. misc Flower colour misc Image analysis misc Image processing misc Machine vision misc RHS colour chart Evaluation of the tepal colour of Begonia x tuberhybrida Voss. for DUS testing using image analysis |
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630 640 ASE 48.58 bkl Evaluation of the tepal colour of Begonia x tuberhybrida Voss. for DUS testing using image analysis Voss. (dpeaa)DE-He213 Flower colour (dpeaa)DE-He213 Image analysis (dpeaa)DE-He213 Image processing (dpeaa)DE-He213 Machine vision (dpeaa)DE-He213 RHS colour chart (dpeaa)DE-He213 |
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ddc 630 bkl 48.58 misc Voss. misc Flower colour misc Image analysis misc Image processing misc Machine vision misc RHS colour chart |
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ddc 630 bkl 48.58 misc Voss. misc Flower colour misc Image analysis misc Image processing misc Machine vision misc RHS colour chart |
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ddc 630 bkl 48.58 misc Voss. misc Flower colour misc Image analysis misc Image processing misc Machine vision misc RHS colour chart |
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Evaluation of the tepal colour of Begonia x tuberhybrida Voss. for DUS testing using image analysis |
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Evaluation of the tepal colour of Begonia x tuberhybrida Voss. for DUS testing using image analysis |
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evaluation of the tepal colour of begonia x tuberhybrida voss. for dus testing using image analysis |
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Evaluation of the tepal colour of Begonia x tuberhybrida Voss. for DUS testing using image analysis |
| abstract |
Abstract In the framework of variety testing, evaluation of the flower of Begonia xtuberhybrida Voss. is done by experts. The colours of the flowers are compared with the RHS colour chart. For each flower colour a code is given. This method has several disadvantages (data cannot be statistically analyzed with standard ANOVA techniques, bias by the expert is possible, difficult measurement depending on the light environment, ...) that can be overcome with image analysis. In this study several parameters were tested to distinguish the different varieties. Varieties were split in different colour groups (white, red and yellow–orange) and parameters were analyzed. Parameters based on the green colour plain of the RGB colour space resulted in the largest discriminating power. Parameters based on the HSV colour space performed less well. |
| abstractGer |
Abstract In the framework of variety testing, evaluation of the flower of Begonia xtuberhybrida Voss. is done by experts. The colours of the flowers are compared with the RHS colour chart. For each flower colour a code is given. This method has several disadvantages (data cannot be statistically analyzed with standard ANOVA techniques, bias by the expert is possible, difficult measurement depending on the light environment, ...) that can be overcome with image analysis. In this study several parameters were tested to distinguish the different varieties. Varieties were split in different colour groups (white, red and yellow–orange) and parameters were analyzed. Parameters based on the green colour plain of the RGB colour space resulted in the largest discriminating power. Parameters based on the HSV colour space performed less well. |
| abstract_unstemmed |
Abstract In the framework of variety testing, evaluation of the flower of Begonia xtuberhybrida Voss. is done by experts. The colours of the flowers are compared with the RHS colour chart. For each flower colour a code is given. This method has several disadvantages (data cannot be statistically analyzed with standard ANOVA techniques, bias by the expert is possible, difficult measurement depending on the light environment, ...) that can be overcome with image analysis. In this study several parameters were tested to distinguish the different varieties. Varieties were split in different colour groups (white, red and yellow–orange) and parameters were analyzed. Parameters based on the green colour plain of the RGB colour space resulted in the largest discriminating power. Parameters based on the HSV colour space performed less well. |
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| container_issue |
1-2 |
| title_short |
Evaluation of the tepal colour of Begonia x tuberhybrida Voss. for DUS testing using image analysis |
| url |
https://dx.doi.org/10.1007/s10681-006-9315-0 |
| remote_bool |
true |
| author2 |
Van Waes, Johan Carlier, Lucien |
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Van Waes, Johan Carlier, Lucien |
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312840098 |
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c |
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| doi_str |
10.1007/s10681-006-9315-0 |
| up_date |
2024-07-04T02:58:07.733Z |
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1803615613986275328 |
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| score |
7.398567 |