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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, <i>Dicentrarchus labrax</i>, and tiger barbs, <i>Puntius tetrazona</i>) 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 <inline-formula> <math display="inline"> <semantics> <mrow> <mn>90</mn> <mo>%</mo> </mrow> </semantics> </math> </inline-formula> of overlaps, and the mean Dice-Sørensen coefficient was around <inline-formula> <math display="inline"> <semantics> <mrow> <mn>0.83</mn> </mrow> </semantics> </math> </inline-formula>. This implies that this method is feasible in real-life applications such as toxicity testing.