Počet záznamů: 1
An Automatic Tortoise Specimen Recognition
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SYSNO ASEP 0471594 Druh ASEP C - Konferenční příspěvek (mezinárodní konf.) Zařazení RIV D - Článek ve sborníku Název An Automatic Tortoise Specimen Recognition Tvůrce(i) Sedláček, Matěj (UTIA-B)
Haindl, Michal (UTIA-B) RID, ORCID
Formanová, D. (CZ)Celkový počet autorů 3 Zdroj.dok. Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications: 21st Iberoamerican Congress, CIARP 2016. - Cham : Springer International Publishing, 2017 / Beltran-Castanon C. ; Nystrom I. ; Famili F. - ISBN 978-3-319-52276-0 Rozsah stran s. 52-59 Poč.str. 8 s. Forma vydání Tištěná - P Akce CIARP 2016 - 21st Iberoamerican Congress 2016 Datum konání 08.11.2016 - 11.11.2016 Místo konání Lima Země PE - Peru Typ akce WRD Jazyk dok. eng - angličtina Země vyd. DE - Německo Klíč. slova Tortoise recognition ; Testudo graeca Vědní obor RIV BD - Teorie informace Obor OECD Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8) CEP GA14-10911S GA ČR - Grantová agentura ČR Institucionální podpora UTIA-B - RVO:67985556 UT WOS 000418399200007 EID SCOPUS 85013427985 DOI 10.1007/978-3-319-52277-7_7 Anotace 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
achieved 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.Pracoviště Ústav teorie informace a automatizace Kontakt Markéta Votavová, votavova@utia.cas.cz, Tel.: 266 052 201. Rok sběru 2018
Počet záznamů: 1