Automatic Image Stitching of Agriculture Areas based on Unmanned Aerial Vehicle using SURF

Ika Widiastuti, Niyalatul Muna, Fendik Eko Purnomo, Faisal Lutfi, Liliek Dwi Soelaksini


Identification  of  agricultural  areas  in  remote  sensing  technology  is  needed  for  the development  of  agricultural  areas.  The  image  of  the  agricultural  area  in  this  study  uses  an Unmanned Air Vehicle (UAV). The results of images taken from a height of 100 meters on the ground will be stored and processed into one image. UAV technology that supports this research is  expected  to  help  remote  sensing  in  real  time.  For  the  current  study,  measurements  in agricultural areas are related to some fragmented images. This article creates a beautiful view of the agricultural region. The author focuses on automatic image milling methods with detection- based image matching and description of patented local features from the dataset. The features method applied is based on speeded up robust features (SURF). The method of matching images and verification results is carried out. The result will create a 2-D spatial reference that starts the panorama size. This paper shows the results of image stitching in the agriculture area.

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