Texture Based Animal Segmentation in Aerial Videos

Article ID

4IQ34

High-quality animal segmentation in videos for enhanced research accuracy.

Texture Based Animal Segmentation in Aerial Videos

Rishaad Abdoola
Rishaad Abdoola Tshwane University of Technology
Yunfei Fang
Yunfei Fang Tshwane University of Technology
Shengzhi Du
Shengzhi Du Tshwane University of Technology
Paul Bartels
Paul Bartels Tshwane University of Technology
Christiaan Oosthuizen
Christiaan Oosthuizen Tshwane University of Technology
DOI

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.

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.

Rishaad Abdoola
Rishaad Abdoola Tshwane University of Technology
Yunfei Fang
Yunfei Fang Tshwane University of Technology
Shengzhi Du
Shengzhi Du Tshwane University of Technology
Paul Bartels
Paul Bartels Tshwane University of Technology
Christiaan Oosthuizen
Christiaan Oosthuizen Tshwane University of Technology

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Rishaad Abdoola. 2026. “. Global Journal of Research in Engineering – A : Mechanical & Mechanics GJRE-A Volume 23 (GJRE Volume 23 Issue A3): .

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Journal Specifications

Crossref Journal DOI 10.17406/gjre

Print ISSN 0975-5861

e-ISSN 2249-4596

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GJRE-A Classification: UDC: 004.896, 591.5, 621.396
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High-quality academic research articles on global topics and journals.

Texture Based Animal Segmentation in Aerial Videos

Rishaad Abdoola
Rishaad Abdoola Tshwane University of Technology
Yunfei Fang
Yunfei Fang Tshwane University of Technology
Shengzhi Du
Shengzhi Du Tshwane University of Technology
Paul Bartels
Paul Bartels Tshwane University of Technology
Christiaan Oosthuizen
Christiaan Oosthuizen Tshwane University of Technology

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