Next Article in Journal
Energy Harvesting Techniques for Wireless Sensor Networks/Radio-Frequency Identification: A Review
Previous Article in Journal
Optimal Incentive Contract for Sales Team with Loss Aversion Preference
Article Menu
Issue 7 (July) cover image

Export Article

Open AccessArticle

Segmentation of Laterally Symmetric Overlapping Objects: Application to Images of Collective Animal Behavior

Institute of Complex Systems, South Bohemian Research Center of Aquaculture and Biodiversity of Hydrocenoses, Kompetenzzentrum MechanoBiologie in Regenerativer Medizin, Faculty of Fisheries and Protection of Waters, University of South Bohemia in České Budějovice, Zámek 136, 373 33 Nové Hrady, Czech Republic
Author to whom correspondence should be addressed.
Symmetry 2019, 11(7), 866;
Received: 5 June 2019 / Revised: 25 June 2019 / Accepted: 27 June 2019 / Published: 3 July 2019
PDF [1629 KB, uploaded 3 July 2019]


Video analysis is currently the main non-intrusive method for the study of collective behavior. However, 3D-to-2D projection leads to overlapping of observed objects. The situation is further complicated by the absence of stall shapes for the majority of living objects. Fortunately, living objects often possess a certain symmetry which was used as a basis for morphological fingerprinting. This technique allowed us to record forms of symmetrical objects in a pose-invariant way. When combined with image skeletonization, this gives a robust, nonlinear, optimization-free, and fast method for detection of overlapping objects, even without any rigid pattern. This novel method was verified on fish (European bass, Dicentrarchus labrax, and tiger barbs, Puntius tetrazona) swimming in a reasonably small tank, which forced them to exhibit a large variety of shapes. Compared with manual detection, the correct number of objects was determined for up to almost 90 % of overlaps, and the mean Dice-Sørensen coefficient was around 0.83 . This implies that this method is feasible in real-life applications such as toxicity testing. View Full-Text
Keywords: image segmentation; lateral objects; 2D vision image segmentation; lateral objects; 2D vision

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

Supplementary material

  • Externally hosted supplementary file 1
    Doi: doi:10.5061/dryad.1j29991

Share & Cite This Article

MDPI and ACS Style

Lonhus, K.; Štys, D.; Saberioon, M.; Rychtáriková, R. Segmentation of Laterally Symmetric Overlapping Objects: Application to Images of Collective Animal Behavior. Symmetry 2019, 11, 866.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics



[Return to top]
Symmetry EISSN 2073-8994 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top