The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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Articles | Volume XL-5/W6
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XL-5/W6, 113–115, 2015
https://doi.org/10.5194/isprsarchives-XL-5-W6-113-2015
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XL-5/W6, 113–115, 2015
https://doi.org/10.5194/isprsarchives-XL-5-W6-113-2015

  18 May 2015

18 May 2015

FUZZY C-MEANS ALGORITHM FOR SEGMENTATION OF AERIAL PHOTOGRAPHY DATA OBTAINED USING UNMANNED AERIAL VEHICLE

M. V. Akinin1, N. V. Akinina1, A. Y. Klochkov2, M. B. Nikiforov3, and A. V. Sokolova3 M. V. Akinin et al.
  • 1Ryazan state radioengineering university, Department of Space Technology, Ryazan, 390005, Gagarina Str. 59/1, Russia
  • 2Ryazan state radioengineering university, Ryazan, 390005, Gagarina Str. 59/1, Russia
  • 3Ryazan state radioengineering university, Department of Electronic Computers, Ryazan,390005, Gagarina Str. 59/1, Russia

Keywords: fuzzy c-means, segmentation, clustering, unmanned aerial vehicle, Xie-Beni index

Abstract. The report reviewed the algorithm fuzzy c-means, performs image segmentation, give an estimate of the quality of his work on the criterion of Xie-Beni, contain the results of experimental studies of the algorithm in the context of solving the problem of drawing up detailed two-dimensional maps with the use of unmanned aerial vehicles. According to the results of the experiment concluded that the possibility of applying the algorithm in problems of decoding images obtained as a result of aerial photography. The considered algorithm can significantly break the original image into a plurality of segments (clusters) in a relatively short period of time, which is achieved by modification of the original k-means algorithm to work in a fuzzy task.