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dc.contributor.authorZhu, S
dc.contributor.authorLi, C
dc.contributor.authorRogers, J
dc.contributor.authorGianni, M
dc.contributor.authorHoward, I
dc.date.accessioned2022-12-17T04:40:21Z
dc.date.available2022-12-17T04:40:21Z
dc.date.issued2021-11-26
dc.identifier.isbn9781665431538
dc.identifier.urihttp://hdl.handle.net/10026.1/20091
dc.description.abstract

The object detection based on computer vision algorithms has a wide range of applications in many domains. This paper introduces a real-time detection methodology of 3D printed double emulsion droplets. The first step is to directly segment and extract the color of the inner droplets from the current field of view using thresholding operations of inRange functions of OpenCV in YUV space, so that the droplets color and background color can be obtained separately. Secondly, a binary masking has been employed to locate the centre of the mass of droplets and also distinguish the droplets from surroundings. Next, the Hough circle transform is used to fit a circle to extract the true edge when identifying the contour of the external droplet. The droplet size, generated frequency, and determine whether the droplet is successfully formed can also be obtained using Hough circle transform. A series of experiments have been conducted and indicated that our proposed detection system works well on different double emulsion microfluidic devices with different background and droplet colors.

dc.format.extent36-41
dc.language.isoen
dc.publisherIEEE
dc.subject46 Information and Computing Sciences
dc.subject40 Engineering
dc.subject4602 Artificial Intelligence
dc.titleA Real-time Double Emulsion Droplets Detection System using Hough Circle Transform and Color Detection
dc.typeconference
dc.typeProceedings Paper
plymouth.author-urlhttps://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000783817900007&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=11bb513d99f797142bcfeffcc58ea008
plymouth.date-start2021-11-26
plymouth.date-finish2021-11-28
plymouth.volume00
plymouth.publisher-urlhttp://dx.doi.org/10.1109/m2vip49856.2021.9665023
plymouth.conference-name2021 27th International Conference on Mechatronics and Machine Vision in Practice (M2VIP)
plymouth.publication-statusPublished
plymouth.journal2021 27th International Conference on Mechatronics and Machine Vision in Practice (M2VIP)
dc.identifier.doi10.1109/m2vip49856.2021.9665023
plymouth.organisational-group/Plymouth
plymouth.organisational-group/Plymouth/Faculty of Science and Engineering
plymouth.organisational-group/Plymouth/Faculty of Science and Engineering/School of Engineering, Computing and Mathematics
plymouth.organisational-group/Plymouth/REF 2021 Researchers by UoA
plymouth.organisational-group/Plymouth/REF 2021 Researchers by UoA/UoA11 Computer Science and Informatics
plymouth.organisational-group/Plymouth/Users by role
plymouth.organisational-group/Plymouth/Users by role/Academics
dc.rights.embargoperiodNot known
rioxxterms.versionofrecord10.1109/m2vip49856.2021.9665023
rioxxterms.licenseref.urihttp://www.rioxx.net/licenses/all-rights-reserved
rioxxterms.typeConference Paper/Proceeding/Abstract


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