Algorithms for Automatic Individual Photo-Identification in Wildlife

Individual Image Recognition in Wildlife - Technical Resources

This site collects articles about the internal processes of AmphIdent and algorithms for pattern matching in wildlife in general. The articles range from general steps and methods for preprocessing images for photo-matching, technical details on the pattern extraction and individual identification, to the description of improvements on the user interface.

Mo, 10 Okt 2016

Artificial Spot Pattern Generation by Machine Learning for Photo-identification of Amphibians

Generating artificial spot patterns to analyze the matching performance of algorithms for image recognition of wildlife can be a viable alternative to relying on huge databases of real patterns with known ground truth. In this article we improve the ability of Markov chain based methods for generating artificial spot patterns …

Di, 12 Jul 2016

Preprocessing for Automatic Pattern Identification in Wildlife: Removing Glare

A common problem for automatic photo-identification of individual animals are specular reflections on the photograps. In particular, species that live in wet areas, like amphibians, or that have a strongly reflecting surface, like fish, snakes or e.g. beetles can produce a significant amount of glare on the photos. At …

Mo, 16 Mai 2016

Artificial Spot Patterns for Performance Analysis of Individual Identification of Animals

To assess the identification performance of pattern recognition for wildlife, a reliable ground truth is absolutely necessary. However, often for field work, no ground truth is available or it can only be obtained by manual comparison with high efforts. This would render the usage of automatic photo-identification of wildlife useless …

Do, 10 Sep 2015

Computer Assisted Photo-Identification - An Overview

The process of computer-aided individual identification of wildlife involves diverse concepts. In general, the following steps are necessary:

  1. Acquisition of photos: This step requires techniques to obtain high-quality digital photos of the species under investigation.
  2. Insertion of the digital photos into a data management system: This step is necessary to …