Hyperspectral Image Dataset
for Individual Penguin Identification

Youta Noboru¹, Yuko Ozasa¹, Masayuki Tanaka²

¹Tokyo Denki University, ²Tokyo Institute of Technology
2024 IEEE International Geoscience and Remote Sensing Symposium

Code arXiv

Experimental Dataset

Full Size Dataset

Examples from the dataset: These RGB images created from the hyperspectral images.

Abstract

Remote individual animal identification is important for food safety, sport, and animal conservation. Numerous existing remote individual animal identification studies have focused on RGB images. In this paper, we tackle individual penguin identification using hyperspectral (HS) images. To the best of our knowledge, it is the first work to analyze spectral differences between penguin individuals using an HS camera. We have constructed a novel penguin HS image dataset, including 990 hyperspectral images of 27 penguins. We experimentally demonstrate that the spectral information of HS image pixels can be used for individual penguin identification. The experimental results show the effectiveness of using HS images for individual penguin identification.

Experimental procedures: (a) Pixels of the target penguins are selected from the captured hyperspectral (HS) images. (b) Pixels selected from the HS images retain information on the wavelength of reflected light. (c) A simple 5-layer MLP is used to predict individual labels of penguins. (d) Individual identification was performed using a single pixel.

Visualisation of classification results: Selection of input pixels with an application in mind and visualization of predicted labels. Pixels of the target with individual label 5 is selected, and the output results are colored differently corresponding to each label.

Classification accuracy for different data types (%).

BibTeX


        @misc{noboru2024hyperspectral,
          title={Hyperspectral Image Dataset for Individual Penguin Identification}, 
          author={Youta Noboru and Yuko Ozasa and Masayuki Tanaka},
          year={2024},
          eprint={2405.14146},
          archivePrefix={arXiv},
          primaryClass={cs.CV}
        }