The Measurement of Color

Marcus, Robert T.

doi:10.1016/s1387-6783(98)80005-6

Cited by 61 publications

(43 citation statements)

References 34 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Pasteurized apple juice purchased in the local market was analyzed for color parameters ( L *, a *, and b*) (Marcus 1998), pH, total soluble solids and total acidity. Total soluble solids (TSS, °Bx) were measured with an ABBE‐3 L refractometer (Milton Roy Co., Rochester, NY) by the AOAC Official Method 932.12 (AOAC 1995).…”

Section: Methodsmentioning

confidence: 99%

See 1 more Smart Citation

REDUCTION OF SACCHAROMYCES CEREVISIAE, ESCHERICHIA COLI AND LISTERIA INNOCUA IN APPLE JUICE BY ULTRAVIOLET LIGHT

Guerrero-Beltrán

Barbosa‐Cánovas

2005

J Food Process Engineering

123

View full text Add to dashboard Cite

Apple juice was inoculated separately with Saccharomyces cerevisiae, Listeria innocua (ATCC 51742) or Escherichia coli (ATCC 11775) for treatment in a double tube ultraviolet (UV) disinfection system. The apple juice was treated at six flow rates (0.073–0.548 L/min) for selected fluences (75–450 kJ/m2). The juice was also inoculated with a mixture of these three microorganisms and UV light treated from 0.548 to 0.735 L/min for 30 min. The microbial reduction was described with a first order kinetic model. Average Duvvalues of 23.1–40.5, 8.2–20.6 and 6.0–17.7 min were obtained for S. cerevisiae, L. innocua and E. coli, respectively. A linear model was used to describe the relationship between log Duvversus flow rate for S. cerevisiae and L. innocua. However, a third order polynomial model was more adequate for describing the E. coli Duvvalues versus flow rate. Less than 10 (no growth), 190 and 200 cfu/mL of S. cerevisiae, L. inocua and E. coli, respectively, were observed in UV‐treated apple juice inoculated with a mixture of microorganisms.

show abstract

Section: Methodsmentioning

confidence: 99%

“…A square white plate was used as a background for measuring color parameters ( L * = 93.2, a * = −0.65, b * = −0.78). The color difference (Δ E *) was calculated as follows (Marcus 1998):…”

Section: Methodsmentioning

confidence: 99%

REDUCTION OF SACCHAROMYCES CEREVISIAE, ESCHERICHIA COLI AND LISTERIA INNOCUA IN APPLE JUICE BY ULTRAVIOLET LIGHT

Guerrero-Beltrán

Barbosa‐Cánovas

2005

J Food Process Engineering

123

View full text Add to dashboard Cite

show abstract

“…The light source was provided by six 100 W/220 V halogen lamps and the object distance between the lens system and the sample was 60 cm. The angle between the camera lens axis and the lighting source axis was 45° because the diffuse reflection responsible for the color occurs at 45° from the incident light (Francis and Clydesdale, 1975;Marcus and Kurt, 1998). The images were acquired using a black background.…”

Section: The Vision Systemmentioning

confidence: 99%

A multispectral vision system to evaluate enzymatic browning in fresh-cut apple slices

Lunadei

Galleguillos

Diezma

et al. 2011

Postharvest Biology and Technology

View full text Add to dashboard Cite

Keywords:Fresh-cut apples Enzymatic browning CIÉ L*a*f>* color space Multispectral images Image analysisThe main objective of this study was to develop a visión system that is able to classify fresh-cut apple slices according to the development of enzymatic browning. The experiment was carried out on 'Granny Smith' apple slices stored at 7.5 °C for 9 days (n = 120). Twenty-four samples were analyzed per day: at zero time and after storage for 1, 3, 7 and 9 days, which corresponds to treatments to, ti, h, ti and t% respectively. Multispectral images were acquired from the samples by employing a 3-CCD camera centered at the infrared (IR, 800nm), red (R, 680nm) and blue (B, 450nm) wavelengths. Apple slices were evaluated visually according to a visual color scale of 1 -5 (where 1 corresponds to fresh samples without any browning and 5 to samples with severe discoloration), to obtain a sensory evaluation Índex (¡SE) for each sample. Finally, for each sample and for each treatment, visible (VIS) relative reflectance spectra (360-740 nm) were obtained. In order to identify the most related wavelengths to enzymatic browning evolution, unsupervised pattern recognition analysis of VIS reflectance spectra was performed by principal components analysis (PCA) on the autoscaled data. Máximum loading valúes corresponding to the B and R áreas were observed. Therefore, a classification procedure was applied to the relative histograms of the following monochromatic images (virtual images), which were computed pixel by pixel: (R-B)/(R + B),R-B and B/R. Inall cases,a non-supervised classification procedure was able to genérate three image-based browningreference classes (BRC): Cluster A (corresponding to the to samples), ClusterB (ti andt3 samples) and Cluster C(t7 and tg samples). Aninternal and anexternal validation (n = 120) were carried out, and the best classifications were obtained with the (R -B)/(R + B) and B/R image histograms (internal validation: 99.2% of samples correctly classified for both virtual images; external validation: 84% with (R -B)/(R + B) and 81% with B/R). The camera classification was evaluated according to the colorimetric measurements, which were usually utilized to evalúate enzymatic browning development (CIÉ L'a'b* color parameters and browning Índex, BI) and according to ¡SE-For both validation phases a*, b*, BI and ¡SE increased while I* valúes decreased with image-based class number, thereby reflecting their browning state.

show abstract

“…Colour parameters were calculated using the CIE L*a*b colour space system [24,25], in which L* is the lightness variable, and chromaticity coordinates are represented by a* (redness/greenness) and b* (yellowness). Colour measurements were performed using a diffuse CIE standard ''D65'' illuminant, at an angle of observation of 10°.…”

Section: Cie L*a*b Colour Parametersmentioning

confidence: 99%

Hyperspectral imaging coupled with chemometric analysis for non-invasive differentiation of black pens

et al. 2016

View full text Add to dashboard Cite

Differentiation of the written text can be performed with a non-invasive and non-contact tool that connects conventional imaging methods with spectroscopy. Hyperspectral imaging (HSI) is a relatively new and rapid analytical technique that can be applied in forensic science disciplines. It allows an image of the sample to be acquired, with full spectral information within every pixel. For this paper, HSI and three statistical methods (hierarchical cluster analysis, principal component analysis, and spectral angle mapper) were used to distinguish between traces of modern black gel pen inks. Non-invasiveness and high efficiency are among the unquestionable advantages of ink differentiation using HSI. It is also less time-consuming than traditional methods such as chromatography. In this study, a set of 45 modern gel pen ink marks deposited on a paper sheet were registered. The spectral characteristics embodied in every pixel were extracted from an image and analysed using statistical methods, externally and directly on the hypercube. As a result, different black gel inks deposited on paper can be distinguished and classified into several groups, in a non-invasive manner.

show abstract

The Measurement of Color

Cited by 61 publications

References 34 publications

REDUCTION OF SACCHAROMYCES CEREVISIAE, ESCHERICHIA COLI AND LISTERIA INNOCUA IN APPLE JUICE BY ULTRAVIOLET LIGHT

REDUCTION OF SACCHAROMYCES CEREVISIAE, ESCHERICHIA COLI AND LISTERIA INNOCUA IN APPLE JUICE BY ULTRAVIOLET LIGHT

A multispectral vision system to evaluate enzymatic browning in fresh-cut apple slices

Hyperspectral imaging coupled with chemometric analysis for non-invasive differentiation of black pens

Contact Info

Product

Resources

About