Classification accuracy improvement of laser-induced breakdown spectroscopy based on histogram of oriented gradients features of spectral images

Jiujiang Yan, Ping Yang, Zhongqi Hao, Ran Zhou, Xiangyou Li, Shisong Tang, Yun Tang, Xiaoyan Zeng, Yongfeng Lu

Research output: Contribution to journalArticlepeer-review

14 Scopus citations

Abstract

To improve the classification accuracy of laser-induced breakdown spectroscopy (LIBS), image histogram of oriented gradients (HOG) features method (IHFM) for materials analysis was proposed in this work. 24 rice (Oryza sativa L.) samples were carried out to verify the proposed method. The results showed that the classification accuracy of rice samples by the full-spectra intensities method (FSIM) and IHFM were 60.25% and 81.00% respectively. The classification accuracy was obviously improved by 20.75%. Universality test results showed that this method also achieved good results in the plastics, steel, rock and minerals classification. This study provides an effective method to improve the classification performance of LIBS.

Original languageEnglish (US)
Pages (from-to)28996-29004
Number of pages9
JournalOptics Express
Volume26
Issue number22
DOIs
StatePublished - Oct 29 2018

ASJC Scopus subject areas

  • Atomic and Molecular Physics, and Optics

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