The ROI of rice planthopper by image processing

Tsung Han Tsai, Ting Yu Lee, Po Hsun Chen

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

5 Scopus citations

Abstract

Rice Planthopper (RPH) infestation in paddy field is a serious disaster in Asia every year. Finding RPHs based on image processing is an important thing before RPHs growth. We propose a region of interest (ROI) method to detect RPHs clearly. First, get rectangle ROI in HSV space and do color analysis. By using decision tree algorithm, classify analytic data to get binary image of RPHs. The results are useful to reduce executing time and loading and obtain image of RPHs.

Original languageEnglish
Title of host publicationProceedings of the 2017 IEEE International Conference on Applied System Innovation
Subtitle of host publicationApplied System Innovation for Modern Technology, ICASI 2017
EditorsTeen-Hang Meen, Artde Donald Kin-Tak Lam, Stephen D. Prior
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages126-129
Number of pages4
ISBN (Electronic)9781509048977
DOIs
StatePublished - 21 Jul 2017
Event2017 IEEE International Conference on Applied System Innovation, ICASI 2017 - Sapporo, Japan
Duration: 13 May 201717 May 2017

Publication series

NameProceedings of the 2017 IEEE International Conference on Applied System Innovation: Applied System Innovation for Modern Technology, ICASI 2017

Conference

Conference2017 IEEE International Conference on Applied System Innovation, ICASI 2017
Country/TerritoryJapan
CitySapporo
Period13/05/1717/05/17

Keywords

  • Image processing
  • Rice planthopper (RPH)
  • ROI

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