Publication details

An Automatic Tortoise Specimen Recognition

Conference Paper (international conference)

Sedláček Matěj, Haindl Michal, Formanová D.

serial: Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications: 21st Iberoamerican Congress, CIARP 2016, p. 52-59 , Eds: Beltran-Castanon C., Nystrom I., Famili F.

action: CIARP 2016 - 21st Iberoamerican Congress 2016, (Lima, PE, 20161108)

project(s): GA14-10911S, GA ČR

keywords: Tortoise recognition, Testudo graeca

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abstract (eng):

The spur-thighed tortoise ({\it Testudo graeca}) is listed among endangered species on the CITES list and the need to keep track of its specimens calls for a noninvasive, reliable and fast method that would recognize individual tortoises one from another. We present an automatic system for the recognition of tortoise specimen based on variable-quality digital photographs of their plastrons using an image classification approach and our proposed discriminative features. The plastron image database, on which the recognition system was tested, consists of 276 low-quality images with a variable scene set-up and of 982 moderate-quality images with a fixed scene set-up. The \nachieved overall success rates of automatically identifying a tortoise in the database were 43,0\% for the low-quality images and 60,7\% for the moderate-quality images. The results show that the automatic tortoise recognition based on the plastron images is feasible and suggests further improvements for a real application use.