Texture Based Animal Segmentation in Aerial Videos

Authors

  • Rishaad Abdoola

  • Yunfei Fang

  • Shengzhi Du

  • Paul Bartels

  • Christiaan Oosthuizen

DOI:

https://doi.org/10.34257/GJREAVOL23IS3PG1

Keywords:

image segmentation, GLCM, texture analysis, animal tracking, animal segmentation

Abstract

Animal detection in aerial videos is a challenging problem due to the complex nature of the scenes involved as well as the natural ability of the animals to camouflage their environment To assist with the detection and classification of animals for the purpose of nature conservation management texture analysis is applied to aerial videos of wildlife scenes to segment the environment from the animals To perform automatic wildlife surveying and animal monitoring it is proposed to use GLCM texture segmentation to reduce the search area for animals in the aerial videos Using the texture in the scene the issues of a moving background and unpredictable state of the animal are avoided The method presented is well suited to implementation on a UAV as it is easily parallelizable

How to Cite

Rishaad Abdoola, Yunfei Fang, Shengzhi Du, Paul Bartels, & Christiaan Oosthuizen. (2023). Texture Based Animal Segmentation in Aerial Videos. Global Journals of Research in Engineering, 23(A3), 1–6. https://doi.org/10.34257/GJREAVOL23IS3PG1

Texture Based Animal Segmentation in Aerial Videos

Published

2023-08-22