Quantitative characterization of surface deformation in polymer composites using digital image analysis

1996 ◽  
Vol 36 (2) ◽  
pp. 298-304 ◽  
Author(s):  
Robert S. Kody ◽  
David C. Martin
Keyword(s):  
Image Analysis ◽  
Polymer Composites ◽  
Digital Image ◽  
Digital Image Analysis ◽  
Surface Deformation ◽  
Quantitative Characterization

scholarly journals Morphology Characterization of Pitting Corrosion on Sensitized Austenitic Stainless Steel by Digital Image Analysis

10.5772/57256 ◽  
2014 ◽  
Author(s):  
Rosinei Batista ◽  
Gilbert Silva ◽  
Antnio Henriques Araujo ◽  
Nelson Tavares ◽  
Jos Wilson De Jesus Silva ◽  
...  
Keyword(s):  
Stainless Steel ◽  
Image Analysis ◽  
Austenitic Stainless Steel ◽  
Digital Image ◽  
Pitting Corrosion ◽  
Digital Image Analysis ◽  
Morphology Characterization

Model-based frequency response characterization of a digital-image analysis system for epifluorescence microscopy

1992 ◽  
Vol 31 (8) ◽  
pp. 1083
Author(s):  
Rajeeb Hazra ◽  
Charles L. Viles ◽  
Stephen K. Park ◽  
Stephen E. Reichenbach ◽  
Michael E. Sieracki
Keyword(s):  
Image Analysis ◽  
Frequency Response ◽  
Digital Image ◽  
Digital Image Analysis ◽  
Epifluorescence Microscopy ◽  
Image Analysis System ◽  
Model Based ◽  
Analysis System ◽  
Digital Image Analysis System

Characterization of Aphid Pathogenic Species in the Genus Pandora by PCR Techniques and Digital Image Analysis

Mycologia ◽  
2001 ◽  
Vol 93 (5) ◽  
pp. 864 ◽  
Author(s):  
Charlotte Nielsen ◽  
Christian Sommer ◽  
Jorgen Eilenberg ◽  
Karen S. Hansen ◽  
Richard A. Humber
Keyword(s):  
Image Analysis ◽  
Digital Image ◽  
Digital Image Analysis ◽  
Pathogenic Species ◽  
Pcr Techniques

scholarly journals Characterization of the Curcuminoids Fingerprint Profile in Curcuma and Zingiber Genera by TLC – Digital Image Analysis

2019 ◽  
Vol 8 (2) ◽  
pp. 147-161
Author(s):  
Anisa Lailatusy Syarifah ◽  
◽  
Rurini Retnowati ◽  
Hermin Sulistyarti
Keyword(s):  
Image Analysis ◽  
Thin Layer ◽  
Digital Image ◽  
Mobile Phase ◽  
Digital Image Analysis ◽  
Curcuma Longa ◽  
Yellow Color ◽  
Zingiber Cassumunar ◽  
Layer Chromatography

Curcuma longa, C. xanthorrhiza, C. heyneana, and Zingiber cassumunar contain high curcuminoid and have relatively similar yellow color. Therefore, they are potentially adulterated and difficult to differentiate in the form of powder. Hence, it is necessary to characterize the fingerprints compound profile by a simple and rapid method. This research aims to determine fingerprint compound profile of curcuminoid using Thin Layer Chromatography (TLC) and digital image analysis. The result of the research identified that the fingerprint compound profile of curcuminoid on the four rhizomes was obtained by TLC method using silica gel 60 GF254 as the stationary phase, chloroform: dichloromethane: methanol (13:6:1) as the mobile phase, and observation under UV 254 nm light and citroborate reagent. Thereafter, the digital image analysis was carried out using Image J software according to the gray value and % of RGB (red-green-blue) value. Based on gray value and % of RGB, both Curcuma and Zingiber genera were differentiated through curcumin compound (Rf 0.63), demethoxycurcumin (Rf 0.34), bisdemethoxycurcumin (Rf 0.21). The profile of fingerprint compound on Curcuma longa, C. xanthorrhiza, C. heyneana, and Zingiber cassumunar was differentiated through Rf 0.26; Rf 0.17; and Rf 0.10.

Sign in / Sign up

Export Citation Format

Share Document