Improving pesticide residues detection using band prioritization and constrained energy minimization

Kenneth Yeonkong Ma, Yi Mei Kuo, Yen Chieh Ouyang, Chgein I. Chang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Citations (Scopus)

Abstract

This paper presents an emerging method to detect pesticide residues on fruit. In order to enhance pesticide signature intensity and make the detection rate of pesticide better, we applied band weighting process and band selection (BS) process base on band prioritization (BP) and band decorrelation (BD) to adjust spectral data. Then four algorithms were used, spectral information divergence (SID), orthogonal subspace projection (OSP), constrained energy minimization (CEM), and support vector machine (SVM) to identify pesticide residues on different fruit. The results show that using CEM method has the highest detection rate of pesticide and has the potential to replace the other traditional methods.

Original languageEnglish
Title of host publication2017 IEEE International Geoscience and Remote Sensing Symposium
Subtitle of host publicationInternational Cooperation for Global Awareness, IGARSS 2017 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages4802-4805
Number of pages4
ISBN (Electronic)9781509049516
DOIs
Publication statusPublished - 2017 Dec 1
Event37th Annual IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2017 - Fort Worth, United States
Duration: 2017 Jul 232017 Jul 28

Publication series

NameInternational Geoscience and Remote Sensing Symposium (IGARSS)
Volume2017-July

Other

Other37th Annual IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2017
Country/TerritoryUnited States
CityFort Worth
Period17-07-2317-07-28

All Science Journal Classification (ASJC) codes

  • Computer Science Applications
  • General Earth and Planetary Sciences

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