Green citrus detection using ‘eigenfruit’, color and circular Gabor texture features under natural outdoor conditions

Kurtulmuş, Ferhat; Lee, Won Suk; Vardar, Ali

doi:10.1016/j.compag.2011.07.001

Cited by 135 publications

(73 citation statements)

References 20 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…The methods used in this article are rather basic compared with methods used for apple detection, which may elucidate why those authors achieved a better performance. However, for green citrus detection, Kurtulmus et al (2011) achieved a TPR of 75% and a SFPR of 27%, which is comparable to results achieved in this research.…”

Section: Discussionsupporting

confidence: 86%

Pixel classification and post-processing of plant parts using multi-spectral images of sweet-pepper

Bac

Hemming

Henten

2013

IFAC Proceedings Volumes

View full text Add to dashboard Cite

Section: Discussionsupporting

confidence: 86%

Pixel classification and post-processing of plant parts using multi-spectral images of sweet-pepper

Bac

Hemming

Henten

2013

IFAC Proceedings Volumes

View full text Add to dashboard Cite

“…Granitto et al 2002, Mebatsion et al 2013, fruits (e.g. Kondo et al 2000, Kurtulmus et al 2011, Mollazade et al 2012, Rodríguez-Pulido et al 2012, Payne et al 2013, leaves (e.g. Buschmann andNagel 1993, Buschmann et al 2012) or entire plants or vegetation (e.g.…”

Section: ---mentioning

confidence: 98%

Measurements of reflectance and fluorescence spectra for nondestructive characterizing ripeness of grapevine berries

Navrátil¹,

Buschmann²

2016

Photosynt.

View full text Add to dashboard Cite

In vivo reflectance and fluorescence spectra from berry skins of a white (Riesling) and red (Cabernet Sauvignon) grapevine variety were measured during a ripening season with a new CMOS radiometer instrument. Classical reference measurements were also carried out: sugar content of the berry juice [°Brix], pigment content (chlorophyll a and b, carotenoids, anthocyanins) from methanol extracts of the berry skin. We showed that the spectra and the colors analyzed from them could be taken as an unambiguous indicator of grapevine ripening. Reflectance spectra, which were affected by the content of pigments (chlorophylls and anthocyanins), effects of surface (wax layers), and tissue structure (cell size) of the berries well correlated (R 2 = 0.89) with the °Brix measurements of the berries. The fast data acquisition of both reflectance and fluorescence spectra in one sample with our radiometer instrument made it superior over the timeconsuming, traditional, and mostly destructive chemical analysis used in vine growing management.

show abstract

“…Numerous studies have used texture analysis in fruit detection methods (Rakun et al, 2011;Zhao et al, 2005;Kurtulmus et al, 2011;Chaivivatrakul and Dailey, 2014). Kurtulmus et al (2011) used Gabor texture analysis proposed by Zhang et al (2002) to segment green citrus from the background.…”

Section: Texture Featuresmentioning

confidence: 99%

Sensors and systems for fruit detection and localization: A review

Gongal

Amatya

Karkee

et al. 2015

Computers and Electronics in Agriculture

451

244

View full text Add to dashboard Cite

Green citrus detection using ‘eigenfruit’, color and circular Gabor texture features under natural outdoor conditions

Cited by 135 publications

References 20 publications

Pixel classification and post-processing of plant parts using multi-spectral images of sweet-pepper

Pixel classification and post-processing of plant parts using multi-spectral images of sweet-pepper

Measurements of reflectance and fluorescence spectra for nondestructive characterizing ripeness of grapevine berries

Sensors and systems for fruit detection and localization: A review

Contact Info

Product

Resources

About