Computer image analysis of seed shape and seed color for flax cultivar description

Wiesnerová, D.; Wiesner, I.

doi:10.1016/j.compag.2007.10.001

Cited by 84 publications

(40 citation statements)

References 12 publications

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“…Therefore, the colour evaluation in this study was performed using a digital colour meter. The seed lots were classified according to the seed coat colour using the image analysis method in flax (Dana and Ivo, 2008) and Ambrosia trifida (Sako et al, 2001) species. Our research showed that this method can be used to classify red clover seed lots according to the seed coat colour.…”

Section: Resultsmentioning

confidence: 99%

Effects of seed coat colour on the seed quality and initial seedling growth of red clover cultivars (Trifolium pratense)

Velijević¹,

Štrbanović²,

Poštić³

et al. 2017

J Process Energy Agric

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The objective of this study was to investigate the influence of seed coat colour on the seed quality of four red clover cultivars (germination, dormancy (hard seeds) REZIME Cilj istraživanja bio je da se ispita uticaj boje semena četiri sorte crvene deteline proizvedene u Srbiji tokom dve godine na njihov kvalitet (klijanje, dormantnost (tvrdo seme), mrtvo seme i početni porast klijanaca (vigor)). U ovom istraživanju su prvo vizuelno razdvojena semena po boji, a zatim su razdvojena digitalnim kolor separatorom na svetla, tamna i mešovita. Rezultati su pokazali da

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Section: Resultsmentioning

confidence: 99%

Effects of seed coat colour on the seed quality and initial seedling growth of red clover cultivars (Trifolium pratense)

Velijević¹,

Štrbanović²,

Poštić³

et al. 2017

J Process Energy Agric

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“…The color model most often used is the RGB model in which an imaging sensor captures the light intensity of the red (R), green (G), and blue (B) components, respectively. RGB, HSV (hue, saturation, and value), and CIELab are the most popular space color models used in food computer vision (Dana and Ivo 2008;Du and Sun 2005;Kang et al 2008;Leemans et al 1998;Leon et al 2006;Magdic and Dobricevic 2007;Mendoza et al 2006;Misimi et al 2007;O'Sullivan et al 2003;Sun 2004;Zhang et al 2003;Zhou et al 2004), among others. The RGB color model is used for computer color representation.…”

Section: Methodsmentioning

confidence: 99%

Color of Salmon Fillets By Computer Vision and Sensory Panel

Quevedo

Aguilera

Pedreschi

2008

Food Bioprocess Technol

147

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A computer vision method was developed and used to assign color score in salmon fillet according to SalmonFan™ card. The methodology was based on the transformation of RGB to L*a*b* color space. In the algorithm, RGB values assigned directly to each pixel by the camera in the salmon fillet image, were transformed to L*a*b* values, and then matched with other L*a*b* values that represent a SalmonFan score (between 20 and 34). Colors were measured by a computer vision system (CVS) and a sensorial panel (eight panelists) under the same illumination conditions in ten independent sets of experiments. Errors from transformation of RGB to L*a*b* values by the CVS were 2.7%, 1%, and 1.7%, respectively, with a general error range of 1.83%. The coefficient of correlation between the SalmonFan score assigned by computer vision and the sensory panel was 0.95. Statistical analysis using t test was performed and showed that there were no differences in the measurements of the SalmonFan score between both methods (t c =1.65 ≤ t=1.96 at α= 0.05%). The methodology presented in this paper is very versatile and can potentially be used by computer-based vision systems in order to qualify salmon fillets based on color according to the SalmonFan card.

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“…RGB based image analysis has been applied in agriculture for various purposes such as weed identification (Hemming and Rath 2000), weed and crop mapping (Tillet et al 2001), weed and crop discrimination (Aitkenhead et al 2003), quantification of turf grass color (Karcher and Rechardson 2003), quantitative analysis of specially variable physiological process across leaf surface (Aldea et al 2006), weed recognition (Ahmad et al 2006) and seed color test for identification of commercial seed traits (Dana and Ivo 2008). In plant tissue culture, RGB based image analysis has been restricted to identification and estimation of shoot length (Honda et al 1997), secondary metabolite determination in hairy root cultures (Berzin et al 1999) and clustering of regenerated plants into groups (Mahendra et al 2004;Prasad and Dutta Gupta 2008).…”

Section: Introductionmentioning

confidence: 99%

Estimation of the chlorophyll content of micropropagated potato plants using RGB based image analysis

Yadav

Ibaraki

Gupta

2009

Plant Cell Tiss Organ Cult

125

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A method has been developed for rapid and non invasive determination of chlorophyll content of leaves of micropropagated potato plants using RGB based image analysis. Among the trichomatic colors, R and G negatively correlated with the chlorophyll content, while a positive correlation was observed with B chromate. Compared to mean brightness value, the use of mean brightness ratio considerably improved the relationship of the tricolors with chlorophyll content. The brightness values and ratios of the primary colors are modeled as linear correlation functions for chlorophyll content. A significant correlation was observed between the model predicted chlorophyll content with the chlorophyll content measured by chlorophyll content meter. Spectral properties such as luminosity and saturation were also found to be negatively correlated with the chlorophyll content. The relationship was improved by combining the mean brightness ratio at B band region with luminosity. The potential of the imaging system in micropropagation has been discussed.

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Computer image analysis of seed shape and seed color for flax cultivar description

Cited by 84 publications

References 12 publications

Effects of seed coat colour on the seed quality and initial seedling growth of red clover cultivars (Trifolium pratense)

Effects of seed coat colour on the seed quality and initial seedling growth of red clover cultivars (Trifolium pratense)

Color of Salmon Fillets By Computer Vision and Sensory Panel

Estimation of the chlorophyll content of micropropagated potato plants using RGB based image analysis

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