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Automatic Detection and Segmentation of Orchards Using Very High-Resolution Imagery
 

Summary: 1
Automatic Detection and Segmentation of Orchards
Using Very High-Resolution Imagery
Selim Aksoy, Senior Member, IEEE, Ismet Zeki Yalniz, Kadim Tas¸demir, Member, IEEE
Abstract--Spectral information alone is often not sufficient
to distinguish certain terrain classes such as permanent crops
like orchards, vineyards, and olive groves from other types of
vegetation. However, instances of these classes possess distinctive
spatial structures that can be observable in detail in very
high spatial resolution images. This paper proposes a novel
unsupervised algorithm for the detection and segmentation of
orchards. The detection step uses a texture model that is based on
the idea that textures are made up of primitives (trees) appearing
in a near-regular repetitive arrangement (planting patterns). The
algorithm starts with the enhancement of potential tree locations
by using multi-granularity isotropic filters. Then, the regularity of
the planting patterns is quantified using projection profiles of the
filter responses at multiple orientations. The result is a regularity
score at each pixel for each granularity and orientation. Finally,
the segmentation step iteratively merges neighboring pixels and

  

Source: Aksoy, Selim - Department of Computer Engineering, Bilkent University

 

Collections: Computer Technologies and Information Sciences