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Selected Publication:

Burgstaller, S; Gollmann, G; Landler, L.
(2021): The Green Toad example: a comparison of pattern recognition software
NORTH-WEST J ZOOL. 2021; 17(1), e211506 96-99.

Individual identification of animals is important for assessing the size and status of populations. Photo-based approaches, where animals are recognized by naturally occurring and visually identifiable features, such as color patterns, are cost-effective methods for this purpose. We compared five available programs (Wild-ID, Hotspotter, Amphldent, APHIS, I3S Pattern+) for their power to semi-automatically identify dorsal patterns of the European green toad (Bufotes viridis). We created a data set of 200 pictures of known identity, two pictures for each individual, and analyzed the percentage of correctly identified animals for each software. Furthermore, we employed a generalized linear mixed model to identify important factors contributing to correct identifications. We used these results to estimate the population size of our hypothetical population. The freely available HotSpotter application performed best, identifying close to 100 % of the photos correctly. Females had a higher chance of recognition, presumably because of sex-specific differences in the pattern contrast. Population estimates were close to the expected 100 for HotSpotter, but for the other applications population size was highly overestimated. Given the clarity of our results we strongly recommend the HotSpotter software, which is a highly efficient tool for individual pattern recognition.
Authors BOKU Wien:
Burgstaller Stephan
Landler Lukas

Find related publications in this database (Keywords)
color pattern
photo-identification software
population statistics
recapture study

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