Development of a morphological color image processing algorithm for paper-based analytical devices

Highlights [Display omitted] Although fabrication of colorimetric paper-based analytical devices (PADs) has drawn increasing attention recently, the signal readout method is still a crucial challenge on the way to practical exploitations. We herein introduce an integration of digital image processin...

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Veröffentlicht in:Sensors and actuators. B, Chemical Jg. 322; S. 128571
Hauptverfasser: Hamedpour, Vahid, Oliveri, Paolo, Malegori, Cristina, Minami, Tsuyoshi
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Lausanne Elsevier B.V 01.11.2020
Elsevier Science Ltd
Schlagworte:
Algorithms
Ammonia
Automatic signal readout
Color imagery
Colorimetry
Data analysis
Digital imaging
Image processing
Isoniazid
Mathematical morphological image processing algorithm
Mathematical morphology
Nanoparticles
Outliers (statistics)
Paper-based analytical devices
Polyvinyl alcohol
Prediction models
Regression analysis
Robustness (mathematics)
Signal processing
Silver
Mathematical morphological image processing algorithm
Paper-based analytical devices
Isoniazid
Automatic signal readout
ISSN:0925-4005, 1873-3077
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Zusammenfassung:Highlights [Display omitted] Although fabrication of colorimetric paper-based analytical devices (PADs) has drawn increasing attention recently, the signal readout method is still a crucial challenge on the way to practical exploitations. We herein introduce an integration of digital image processing with a model PAD for easing and improving the signal readout procedure. The colorimetric detection mechanism of PAD relies on in-situ induced yellowish silver nanoparticles via the interaction of silver ions, poly(vinyl alcohol), and ammonia with isoniazid. The observed color value is related with the concentration of isoniazid. The proposed algorithm is based on mathematical morphology recognition, and minimizes the errors arising from manual area selection. Besides, it allows the recognition of both circle and square shapes in 96-well plate and A4 size array designs. Since this algorithm automatically provides the blank-corrected numerical matrixes and image profiles of red, green and blue channels, further investigations such as outlier classification, construction of regression/prediction models and calculation of detection limit can be easily performed. Comparison of signal readout results of the developed algorithm with ImageJ software demonstrates significant improvements in analysis speed, reproducibility, accuracy and color values. Therefore, application of the proposed algorithm is promising as a robust technique for practical applications.
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ISSN:0925-4005
1873-3077
DOI:10.1016/j.snb.2020.128571