scholarly journals Geometric Method for Estimating Coral Surface Area Using Image Analysis v1 (protocols.io.bpxcmpiw)

protocols.io ◽  
2020 ◽  
Author(s):  
Rowan Mclachlan ◽  
Andrea G
Keyword(s):  
Image Analysis ◽  
Surface Area ◽  
Geometric Method ◽  
Coral Surface

A study of using a simple 2D image analysis method to monitor the surface area of hypertrophic scars on hand during pressure therapy

Burns ◽  
2020 ◽  
Vol 46 (7) ◽  
pp. 1548-1555
Author(s):  
Annie Yu ◽  
Kit Lun Yick ◽  
Sun Pui Ng ◽  
Joanne Yip ◽  
Ying Fan Chan
Keyword(s):  
Image Analysis ◽  
Surface Area ◽  
Hypertrophic Scars ◽  
Analysis Method ◽  
Image Analysis Method ◽  
Pressure Therapy

Effects of resolution on the measurement of grain ‘size’

1985 ◽  
Vol 49 (353) ◽  
pp. 539-546 ◽  
Author(s):  
R. Dearnley
Keyword(s):  
Grain Size ◽  
Image Analysis ◽  
Grain Boundary ◽  
Surface Area ◽  
Unit Volume ◽  
Fractal Dimensions ◽  
Size Analysis ◽  
Automatic Image Analysis ◽  
Fine Grained ◽  
Kinetics Of

AbstractMeasurements of fine-grained dolerites by optical automatic image analysis are used to illustrate the effects of magnification and resolution on the values obtained for grain ‘size’, grain boundary length, surface area per unit volume, and other parameters. Within the measured range of optical magnifications (× 26 to × 3571) and resolutions (1.20 × 10−3 cm to 8.50 × 10−6 cm), it is found that the values of all grain parameters estimated by chord size analysis vary with magnification. These results are interpreted in terms of the concepts of ‘fractal dimensions’ introduced by Mandelbrot (1967, 1977). For some comparative purposes the fractal relationships may be of little significance as relative changes of size, surface area, and other parameters can be expressed adequately at given magnification(s). But for many studies, for instance in kinetics of grain growth, the actual diameter or surface area per unit volume is an important dimension. The consequences are disconcerting and suggest that it may be difficult in some instances to specify the ‘true’ measurements of various characteristics of fine-grained aggregates.

Analysis of film coating thickness and surface area of pharmaceutical pellets using fluorescence microscopy and image analysis

2000 ◽  
Vol 22 (2) ◽  
pp. 325-339 ◽  
Author(s):  
Martin Andersson ◽  
Björn Holmquist ◽  
Jörgen Lindquist ◽  
Olle Nilsson ◽  
Karl-Gustav Wahlund
Keyword(s):  
Image Analysis ◽  
Fluorescence Microscopy ◽  
Surface Area ◽  
Coating Thickness ◽  
Film Coating

Image analysis of chronic wounds for determining the surface area

2010 ◽  
Vol 18 (4) ◽  
pp. 349-358 ◽  
Author(s):  
Elisabeth S. Papazoglou ◽  
Leonid Zubkov ◽  
Xiang Mao ◽  
Michael Neidrauer ◽  
Nicolas Rannou ◽  
...  
Keyword(s):  
Image Analysis ◽  
Surface Area ◽  
Chronic Wounds

scholarly journals 205 Non-destructive Surface Area Determination of Vegetables

HortScience ◽  
2000 ◽  
Vol 35 (3) ◽  
pp. 426C-426
Author(s):  
M.K. Upadhyaya ◽  
N.H. Furness
Keyword(s):  
Image Analysis ◽  
Surface Area ◽  
Area Measurement ◽  
Image Analysis Technique ◽  
Analysis Technique ◽  
Surface Area Measurement ◽  
Non Destructive ◽  
Surface Area Determination ◽  
Area Determination

Surface area of cucumbers, carrots, parsnips, and beets was determined using the following non-destructive methods: Baugerod's method, Baugerod's method with inclusion of a factor correcting for substitution of weight for volume in the formula, and a novel image analysis method. Accuracy of the methods was ascertained by comparison with a direct shrink-wrap replica method of surface area measurement. Vegetables ranged in shape from cylindrical (cucumber and carrot) to conical (parsnip and beet). No difference in accuracy among methods of surface area determination was detected for carrots or beets. Baugerod's method and the image analysis technique differed significantly from the direct shrink-wrap replica technique for surface area determination of parsnips and cucumbers, respectively. Inclusion of a correction factor in Baugerod's method did not increase the accuracy of this method for any of the vegetables. The precision and repeatability of each method was determined by repeated measures analysis. Baugerod's method lost precision and repeatability for the conically shaped vegetables. Conversely, the shrink-wrap replica method lost precision and repeatability for the cylindrically shaped vegetables. The image analysis technique was precise and highly repeatable over the range of vegetable shapes. The development of a rapid, accurate, and precise non-destructive method of surface area measurement using image analysis techniques will provide a useful tool in the physiological study of vegetable products. Applicability of such a method over a range of vegetable shapes will be of additional value.

scholarly journals Surface Characteristics of Leafy Vegetables and Their Effects on Salmonella Attachment

2020 ◽  
Vol 141 ◽  
pp. 03002
Author(s):  
Chanthima Phungamngoen ◽  
Sriwiang Rittisak
Keyword(s):  
Image Analysis ◽  
Fractal Dimension ◽  
Surface Area ◽  
Measurement Method ◽  
Surface Characteristics ◽  
Ventral Side ◽  
Dorsal Side ◽  
Leafy Vegetable ◽  
Leafy Vegetables ◽  
Lower Side

Leafy vegetables exhibit non-uniform surfaces and are structured with interconnected networks of veinlets or wrinkle characteristics, making the quantification of the changes rather difficult. In this study, attempt was made to quantify the surface topographical features of leafy vegetable. Image analysis was used to determine the characteristic of vegetable surface. In term of surface area (A), the results were compared with those correlated with the data obtained by a conventional measurement method. It was also performed to determine fractal dimension (FD) and roughness value (R) to describe the behavior of bacteria attached on the vegetable surface. The results showed that different leafy vegetable (basil, lemon basil, peppermint and cabbage) did not have a significant effect on Salmonella attached on surface. Dorsal side (upper side) of leaves exhibited higher R and lower FD than ventral side (lower side). It led to number of Salmonella attached on upper side of leaves showed higher than their lower side. From Pearson’s correlation, FD could relate well with the number of Salmonella attached on surface of vegetable. FD showed the highest correlation (-0.78-(-0.97)) follow by A (0.77-0.86) and R (0.61-0.87), respectively. Therefore, the parameters from image analysis were found to be good indicator to describe the physical characteristics of leafy vegetable.

Specific Surface Area by Colorimetry and Image Analysis

2021 ◽  
Vol 45 (1) ◽  
pp. 20210026
Author(s):  
Marisol Salva Ramirez ◽  
J. Carlos Santamarina
Keyword(s):  
Image Analysis ◽  
Specific Surface ◽  
Surface Area ◽  
Specific Surface Area
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