## 5 Conclusions, Limitations, and Future Research  
The present study demonstrated that the identification of fish individuals without obvious patterns on the body from the same species and within a close group (i.e., a tank, cage, or aquarium--in our case, in a tank with a limited number of fish) can be done fully automatically based on images of the fish using image processing methods. We tested our approach on the commercially important fish species of seabass and common carp. Accuracy of 100% was obtained for the short-term identification of both species, and 100% and 80% accuracy were obtained for the long-term identification of seabass and carp, respectively. Different parts of the body, mainly parts featuring scales and the patterns on the operculum of the fish, were tested for identification. The study showed that the chosen patterns can be used for long-term identification, except for patterns on the operculum. The uniqueness of scale patterns was proven, together with their stability during the cultivation period (in our case, the longest period was four months). Our approach reveals that even a fish without obvious patterns on its body (only scale body) could be used for the automatic non-invasive identification of individual fish. Photo identification is thus a possible substitute for commonly used invasive fish tagging identification methods.  
The approach we have used has several limitations that need to be solved in future studies. Such limitations include the position of the ROI, and to cut the ROI precisely enough so as to get the best identification accuracy is still challenging. We tested a maximum of 300 fish individuals, whereas in the tank, the number of fish is much higher. The present approach was tested on two different fish species to demonstrate the generalizability of the method. This approach could be used for the real-time identification of individuals under real conditions in a tank/sea cage, which could be helpful in precision fish farming for controlling and documenting the fish-growth process. Studying this application will be the next step in our complex research. A future study is to test this approach to the real time monitoring of the individual fish in tank, and increase the number of the fish individuals to a thousand.  
D.B. is responsible for the data collection, data processing and manuscript writing. P.C. is responsible for data collection and manuscript writing. All authors have read and agreed to the published version of the manuscript.  
This study was financially supported by the Ministry of Education, Youth and Sports of the Czech Republic--project \"CENAKVA\" (LM2018099), the CENAKVA Centre Development [No. CZ.1.05/2.1.00/19.0380], AQUAEXCEL2020 project (652831) and GAJU 013/2019/Z.  
The animal study protocol was approved by the ethical advisor of the TNA projects under AQUAEXCEL2020 project.  
Not applicable.  
Data available by the request.  
We are thankful to HCMR infrastructure and especially to [PERSON] and [PERSON] for their help during seabass data collection. We also thank [PERSON] for consultations on the pattern formation of fish scales.  
The authors declare no conflict of interest.