Computer Software for Selected Plant Species Segmentation on Airborne Images

  • Sebastian IwaszenkoEmail author
  • Marcin Kelm
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 928)


The usage of manned and unmanned flying devices for aerial images acquisition becomes more and more popular nowadays. Though unmanned aerial vehicles (aka drones) are capable of an easy and efficient gathering of spatial information, there is a growing need for efficient tools supporting its analysis and processing. The software solution presented in this article is aimed at identification and characterization of the selected plant species on industrial waste dumps based on aerial images analysis. The software uses back projection method for segmentation of areas covered by Solidago canadensis (Goldenrod), which is known as an invasive one. The software assists the user in the segmentation of areas covered by the identified plants and characterizing their parameters. The application implements selected methods helping in image preprocessing, segmentation, weed identification and calculation of segmented areas shape parameters. The Solidago canadensis segmentation tests were performed with satisfactory results.



The research presented in the paper have been supported by the statutory activity of the Central Mining Institute: Application of image recognition and machine learning methods for Run-Of-Mine and waste mineral matter characterization – No. GIG: 11010117-144.


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Copyright information

© Springer Nature Switzerland AG 2018

Authors and Affiliations

  1. 1.Central Mining InstituteKatowicePoland
  2. 2.KELM Solutions Marcin KelmKatowicePoland

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