Digital image-based flame emission spectrometry

Lyra, Wellington da Silva; Santos, Vagner Bezerra dos; Dionízio, Amália Geiza Gama; Martins, Valdomiro Lacerda; Almeida, Luciano F.; Gaião, Edvaldo N.; Diniz, Paulo Henrique Gonçalves Dias; Silva, Edvan Cirino

doi:10.1016/j.talanta.2008.09.057

Cited by 59 publications

(19 citation statements)

References 10 publications

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“…These two abovementioned studies 7,8 are typical examples of computer vision-based analytical chemistry (CVAC), 3,5 which generally requires several steps for image processing, such as image segmentation, texture analysis, and/or other mathematical correction operations before statistical or chemometric analysis. Image segmentation consists of the partitioning of a digital image into multiple regions (set of pixels) with no overlapping and is typically used to locate objects and boundaries (lines, curves, etc.)…”

Section: Digital Image-based Chemical Analysismentioning

confidence: 99%

“…In a similar way, Lyra et al 8 explored the atomic emission phenomenon (as classically done in the well-known flame emission spectrometry [FES]) by capturing digital images, which were associated to radiation emitted by the analytes into a flame. They quantified lithium, sodium, and calcium in antidepressive drug, normal saline, and water, respectively, using a webcam as a detector.…”

Section: Digital Image-based Chemical Analysismentioning

confidence: 99%

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Chemometrics‐assisted color histogram‐based analytical systems

Diniz

2020

Journal of Chemometrics

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This review systematizes for the first time the here called "Chemometricsassisted color histogram-based analytical systems" under the acronym CACHAS. A comprehensive discussion of the fundamentals, general characteristics, and applications are presented in order to direct practical aspects for developing methods that use color histograms as input data for the construction of chemometric models. For this, analytical information is rapidly acquired using a simple image acquisition device (such as digital camera, webcam, scanner, or smartphone), without need for any image processing, other than extraction of the histograms, which are constructed by counting the frequency distribution of the different color tones (conveniently specified through a color space) of all pixels delimited by a region of interest in a digital image. As a consequence, CACHAS have been increasingly used for qualitative and quantitative purposes in food, agricultural, forensic, biomedical, and microbiological analysis, reinforcing the principles of green analytical chemistry.

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Section: Digital Image-based Chemical Analysismentioning

confidence: 99%

Section: Digital Image-based Chemical Analysismentioning

confidence: 99%

Chemometrics‐assisted color histogram‐based analytical systems

Diniz

2020

Journal of Chemometrics

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“…The individual RGB intensities for each pixel of a digital colour image can be extracted with various colour analysis programs, such as Matlab [25,27,43], Kylix [33,35], Visual basic [26,28], Corel Draw [27], GIMP [27], and Adobe Photoshop [18][19][20][21]. These programs can extract the individual RGB intensities for each pixel.…”

Section: Colour Analysis Of Digital Imagesmentioning

confidence: 99%

“…The various types of digital cameras for colour imaging include digital single-lens reflex (DSLR) cameras [18][19][20]28], digital compact cameras [26,27,29], built-in cameras in mobile phones [21,22], and webcams [30][31][32][33][34][35]. The use of such cameras as colourimetric detectors lowers the cost of quantitative analysis by avoiding the costs of an expensive spectrophotometer, and webcams in particular are inexpensive and readily accessible.…”

Section: Introductionmentioning

confidence: 99%

On-site semi-quantitative analysis for ammonium nitrate detection using digital image colourimetry

et al. 2015

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“…The CVAC technique has been increasingly used in research laboratories and commercial laboratory equipment for more than two decades [26,[28][29][30][31][32][33][34][35][36][37][38][39][40][41]. Lowcost commercial digital cameras and scanners have been gradually incorporated into the analytical laboratory, where they are being increasingly used for forensic [42,43], telemedicine [27,48] and, obviously, analytical purposes [26,44,46,47,49,50,[53][54][55].…”

Section: Introductionmentioning

confidence: 99%

Computer vision-based analytical chemistry applied to determining iron in commercial pharmaceutical formulations

Solana-Altabella

Sánchez-Iranzo

Bueso-Bordils

et al. 2018

Talanta

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Two different computer vision-based analytical chemistry (CVAC) methods were developed to quantify iron in the commercial pharmaceutical formulations Ferbisol and Ferro sanol. The methods involve using a digital camera or a desktop scanner to capture a digital image of a series of Fe standard solutions and the unknown sample upon reaction with o-phenanthroline. The images are processed with appropriate software (e.g., the public domain programme ImageJ, from NIH) to obtain a numerical value (analytical signal) based on colour intensity. The fact that such a value is proportional to the analyte concentration allows one to construct a calibration graph from the standards and interpolate the value for the sample in order to determine its concentration. The results thus obtained were compared with those provided by a spectrophotometric method and the US Pharmacopoeia's recommended method. The differences never exceeded 2%. The two proposed methods are simple and inexpensive; also, they provide an effective instrumental alternative to spectrophotometric methods which can be especially beneficial in those cases where purchasing and maintaining a spectrophotometer is unaffordable.

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Digital image-based flame emission spectrometry

Cited by 59 publications

References 10 publications

Chemometrics‐assisted color histogram‐based analytical systems

Chemometrics‐assisted color histogram‐based analytical systems

On-site semi-quantitative analysis for ammonium nitrate detection using digital image colourimetry

Computer vision-based analytical chemistry applied to determining iron in commercial pharmaceutical formulations

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