Multi-object recognition in turbid water using compressive sensing

  • Changqing Dong*
  • , Xuemin Cheng
  • , Hongsheng Bi
  • , Qun Hao
  • *Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Recognizing and classifying plankton in low-contrast images is difficult. A clustering algorithm are proposed to classify plankton and counted them on a compressed sensing frame. The reasonable output is proved in the experiment.

Original languageEnglish
Title of host publicationComputational Optical Sensing and Imaging, COSI 2018
PublisherOptica Publishing Group (formerly OSA)
ISBN (Print)9781943580446
DOIs
Publication statusPublished - 2018
EventComputational Optical Sensing and Imaging, COSI 2018 - Orlando, United States
Duration: 25 Jun 201828 Jun 2018

Publication series

NameOptics InfoBase Conference Papers
VolumePart F99-COSI 2018
ISSN (Electronic)2162-2701

Conference

ConferenceComputational Optical Sensing and Imaging, COSI 2018
Country/TerritoryUnited States
CityOrlando
Period25/06/1828/06/18

Fingerprint

Dive into the research topics of 'Multi-object recognition in turbid water using compressive sensing'. Together they form a unique fingerprint.

Cite this