global-journal-of-research-in-engineering-a-mechanical-mechanics Global Journal of Research in Engineering - A : Mechanical & Mechanics 0975-5861 2249-4596 Global Journals Publishing Group Incorporated 55666 Texture Based Animal Segmentation in Aerial Videos UAV Wildlife Detection via Texture Analysis AbdoolaRishaad FangYunfei DuShengzhi BartelsPaul OosthuizenChristiaan SOUTH AFRICA, Tshwane University of Technology 22 08 2023 23 A3 1 6

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.

 image segmentation GLCM texture analysis animal tracking animal segmentation. Full Text

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.