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dc.contributor.authorNguyen, Nam-Trung
dc.contributor.authorTor, Shu Beng
dc.contributor.authorGañán-Calvo, Alfonso M.
dc.contributor.authorLoh, Ngiap Hiang
dc.contributor.authorTan, Say Hwa
dc.contributor.authorChong, Zhuang Jie
dc.date.accessioned2016-10-07T16:57:33Z
dc.date.available2017-03-01T16:14:47Z
dc.date.issued2016-04
dc.date.submitted2015-07
dc.identifier.issn1613-4982
dc.identifier.issn1613-4990
dc.identifier.urihttp://hdl.handle.net/1721.1/104792
dc.description.abstractThis paper identifies and addresses the bottlenecks that hamper the currently available software to perform in situ measurement on droplet-based microfluidic. The new and more universal object-based background extraction operation and automated binary threshold value selection make the processing step of our video processing software (ADM) fully automated. The ADM software, which is based on OpenCV image processing library, is made to perform measurements with high processing speed using efficient code. As the processing speed is higher than the data transfer speed from the video camera to permanent storage of computer, we integrate the camera software development kit (SDK) with ADM. The integration allows simultaneous operations of the video transfer/streaming and the video processing. As a result, the total time for droplet measurement using the new process flow with the integrated program is shortened significantly. ADM is also validated by comparing with both manual analysis and DMV software. ADM will be publicly released as a free tool. The software can also be used on a video file or files without the integration with the camera SDK.en_US
dc.description.sponsorshipSingapore. Ministry of Education (Tier 2 Grant 2011-T2-1-0-36)en_US
dc.publisherSpringer Berlin Heidelbergen_US
dc.relation.isversionofhttp://dx.doi.org/10.1007/s10404-016-1722-5en_US
dc.rightsArticle is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use.en_US
dc.sourceSpringer Berlin Heidelbergen_US
dc.titleAutomated droplet measurement (ADM): an enhanced video processing software for rapid droplet measurementsen_US
dc.typeArticleen_US
dc.identifier.citationChong, Zhuang Zhi et al. “Automated Droplet Measurement (ADM): An Enhanced Video Processing Software for Rapid Droplet Measurements.” Microfluidics and Nanofluidics 20.4 (2016): n. pag.en_US
dc.contributor.departmentSingapore-MIT Alliance in Research and Technology (SMART)en_US
dc.contributor.mitauthorChong, Zhuang Jie
dc.relation.journalMicrofluidics and Nanofluidicsen_US
dc.eprint.versionAuthor's final manuscripten_US
dc.type.urihttp://purl.org/eprint/type/JournalArticleen_US
eprint.statushttp://purl.org/eprint/status/PeerRevieweden_US
dc.date.updated2016-08-18T15:36:41Z
dc.language.rfc3066en
dc.rights.holderSpringer-Verlag Berlin Heidelberg
dspace.orderedauthorsChong, Zhuang Zhi; Tor, Shu Beng; Gañán-Calvo, Alfonso M.; Chong, Zhuang Jie; Loh, Ngiap Hiang; Nguyen, Nam-Trung; Tan, Say Hwaen_US
dspace.embargo.termsNen
mit.licensePUBLISHER_POLICYen_US
mit.metadata.statusComplete


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