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Colour and image processing for output extraction of a LSPR sensor

2022-03-07Conference object Restricted access
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dc.contributor.authorMansour, Rima
dc.contributor.authorStojkovic, Vladan
dc.contributor.authorVygranenko, Yuri
dc.contributor.authorLourenço, Paulo
dc.contributor.authorJesus, Rui
dc.contributor.authorFantoni, Alessandro
dc.date.accessioned2022-03-09T10:59:57Z
dc.date.available2022-03-09T10:59:57Z
dc.date.issued2022-03-07
dc.descriptionEste trabalho foi financiado pelo Concurso Anual para Projetos de Investigação, Desenvolvimento, Inovação e Criação Artística (IDI&CA) 2020 do Instituto Politécnico de Lisboa. Código de referência IPL/2020/AGE-SPReS/ISEL
dc.description.abstractSensors based on the Local Surface plasmon Resonance (LSPR) are attractive due to their simple structure and good sensitivity, but the expensive optoelectronic part of the device is limiting the practical applications. There is a need for new strategies to bring the excellent detection properties of LSPR sensors to the playground of low-cost devices and materials. In this work, it is proposed a novel approach to the output extraction of from LSPR sensor whose sensing element is composed by metal nanoparticles (MNPs). Illuminated with an incident broad light source, the sensor produces a spectral transmission output where the MNPs act like a band-stop optical filter for a specific wavelength. An alteration of the refractive index in the surrounding medium corresponds directly to a shift of the filtering rejection band, which corresponds to a slight change in the colour of the light transmitted by the sensor elements. This colour change can be captured by a CMOS photo-camera, used as an image sensor. It is proposed in this paper an approach based on an automatized image processing algorithm for colour change detection, yielding to a system capable of detecting refractive index variations, avoiding the use of expensive spectrometers. The algorithm comprises three stages: (1) Region of interest detection: images are first cropped using the Otsu threshold binary image to remove the uninteresting areas in the image. (2) Image segmentation: using the watershed algorithm, the sensor elements (sample) area is detected automatically in the cropped image. The segmentation is done using the gradient image, where the watershed markers are the regions of low gradient and barriers are the areas of high values inside the image. (3) The resulted sample region is then processed to find its average or dominant LAB colour and then compare it to its corresponding sample image immersed in different mediums using the colour difference measurement CIEDE2000.pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.citationMANSOUR, Rima; [et al] – Colour and image processing for output extraction of a LSPR sensor. In Proceedings of SPIE 11950, Optics and Biophotonics in Low-Resource Settings VIII. SPIE BiOS, 2022, San Francisco, California, United States (2 March 2022). ISSN 1605-7422. Vol. 11950. Pp. 119500B-1 - 119500B-11.pt_PT
dc.identifier.doi10.1117/12.2607463pt_PT
dc.identifier.issn1605-7422
dc.identifier.urihttp://hdl.handle.net/10400.21/14418
dc.language.isoengpt_PT
dc.publisherSPIEpt_PT
dc.relationPTDC/NAN-OPT/31311/2017 - EU funds through the FEDER European Regional Development Fund and by FCTpt_PT
dc.relationUID/EEA/00066/2020 - EU funds through the FEDER European Regional Development Fund and by FCTpt_PT
dc.relationProjeto financiado no âmbito do Concurso de Projetos de Investigação, Desenvolvimento, Inovação & Criação Artística (IDI&CA) financiados pelo Instituto Politécnico de Lisboa. IPL/2020/AGE-SPReS/ISELpt_PT
dc.subjectLSPR sensorpt_PT
dc.subjectWatershed segmentation algorithmpt_PT
dc.subjectCIELABpt_PT
dc.subjectCIEDE2000pt_PT
dc.titleColour and image processing for output extraction of a LSPR sensorpt_PT
dc.typeconference object
dspace.entity.typePublication
oaire.citation.conferencePlaceSan Francisco, California, United Statespt_PT
oaire.citation.endPage119500B-11pt_PT
oaire.citation.startPage119500B-1pt_PT
oaire.citation.titleOptics and Biophotonics in Low-Resource Settings VIIIpt_PT
oaire.citation.volume11950pt_PT
person.familyNameStojkovic
person.familyNameVygranenko
person.familyNameLourenço
person.familyNameJesus
person.familyNameFantoni
person.givenNameVladan
person.givenNameYuri
person.givenNamePaulo
person.givenNameRui
person.givenNameAlessandro
person.identifier2682439
person.identifier.ciencia-id5E1B-6B95-DD52
person.identifier.ciencia-id121C-05B4-3897
person.identifier.ciencia-id431F-5C2C-00FB
person.identifier.ciencia-id041D-93A6-7412
person.identifier.ciencia-id241E-E87C-552F
person.identifier.orcid0000-0002-1819-5606
person.identifier.orcid0000-0002-8785-445X
person.identifier.orcid0000-0003-1869-6491
person.identifier.orcid0000-0002-9938-0351
person.identifier.ridK-1105-2016
person.identifier.scopus-author-id6701808217
person.identifier.scopus-author-id23012170100
person.identifier.scopus-author-id7006535604
rcaap.rightsclosedAccesspt_PT
rcaap.typeconferenceObjectpt_PT
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