Towards Automated Biometric Identification of Sea Turtles (Chelonia mydas)

Journal of ICT Research and Applications

Aazani Mujahid¹  Irwandi Hipiny²  Hamimah Ujir³ 

[1] Danau Girang Field Centre, Sabah Wildlife Department and Cardiff University, Lower Kinabatangan Wildlife Sanctuary, Sabah,;Faculty of Computer Science and Information Technology, UNIMAS, Jalan Datuk Mohammad Musa, 94300 Kota Samarahan, Sarawak,;Faculty of Resource Science and Technology, UNIMAS, Jalan Datuk Mohammad Musa, 94300 Kota Samarahan, Sarawak,

关键词: content-based image retrieval;    invariant feature descriptor;    multimedia databases;    template matching;    visual animal biometrics.;   

DOI  :  10.5614/itbj.ict.res.appl.2018.12.3.4

学科分类：电子、光学、磁材料

来源: Institute for Research and Community Services ITB

【 摘 要 】

Passive biometric identification enables wildlife monitoring with minimal disturbance. Using a motion-activated camera placed at an elevated position and facing downwards, images of sea turtle carapaces were collected, each belonging to one of sixteen Chelonia mydas juveniles. Then, co-variant and robust image descriptors from these images were learned, enabling indexing and retrieval. In this paper, several classification results of sea turtle carapaces using the learned image descriptors are presented. It was found that a template-based descriptor, i.e. Histogram of Oriented Gradients (HOG) performed much better during classification than keypoint-based descriptors. For our dataset, a high-dimensional descriptor is a must because of the minimal gradient and color information in the carapace images. Using HOG, we obtained an average classification accuracy of 65%. 

【 授权许可】

CC BY