Simplified Classification of Multispectral Image Fragments

Authors

  • A. Lorencs Institute of Electronics and Computer Science
  • I. Mednieks Institute of Electronics and Computer Science
  • J. Sinica-Sinavskis Institute of Electronics and Computer Science

DOI:

https://doi.org/10.5755/j01.eee.20.6.7286

Keywords:

Multispectral imaging, image classification, spectral features

Abstract

A simplified approach to classification of multispectral image fragments by their specific spectral features is presented. Application of this approach to discrimination of vegetation areas occupied by the Giant Hogweed species is described and compared with an approach based on calculation of the Consolidated Covariance Image. The proposed method is based on calculation of mean and standard deviation and successive thresholding within certain spectral bands that are found to be informative for the specific task by analysing the ground truth data. It is shown that the method provides close to perfect discrimination of Giant Hogweed from other vegetation areas represented in ground truth data (absence of commission errors together with clear identification of Giant Hogweed fragments in corresponding ground truth regions). Simplicity of the method provides for fast processing of multispectral images from large areas. The proposed approach is perspective for analysis of multispectral images in different application fields where it is possible to choose several informative spectral bands, e.g. in biomedical imaging.

DOI: http://dx.doi.org/10.5755/j01.eee.20.6.7286

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Published

2014-06-09

How to Cite

Lorencs, A., Mednieks, I., & Sinica-Sinavskis, J. (2014). Simplified Classification of Multispectral Image Fragments. Elektronika Ir Elektrotechnika, 20(6), 136-139. https://doi.org/10.5755/j01.eee.20.6.7286

Issue

Section

SYSTEM ENGINEERING, COMPUTER TECHNOLOGY