Abstract
Skeleton-based forensic identification techniques involve the assessment of human osseous remains to identify the deceased person’s identity and cause of death. Craniofacial superimposition (CFS) is one of the most extended techniques of such kind. It involves the superimposition of an image of a skull with a number of ante-mortem face images of an individual and the analysis of their morphological correspondence. Designing automatic methods to address CFS and support the forensic anthropologist remains a challenge. Our research group has a long-term collaboration track with the University of Granada’s Physical Anthropology Lab and some other international forensic labs to automate the whole CFS identification process. The procedure is affected by different sources of uncertainty and thus fuzzy set theory becomes an appealing approach to automate this task. The current contribution reviews these developments specifically focusing on the fuzzy set-based solutions applied to deal with each of the uncertainty sources inherent to the process.
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Acknowledgements
This work was supported by the Spanish Ministry of Science, Innovation and Universities, and European Regional Development Funds (ERDF) under grant EXASOCO (PGC2018-101216-B-I00), and by the Regional Government of Andalusia under grant EXAISFI (P18-FR-4262). Dr. Ibáñez’s work is funded by Spanish Ministry of Science, Innovation and Universities-CDTI, Neotec program 2019 [reference EXP-00122609/SNEO-20191236]. The results of this work are part of the doctoral thesis in Biomedicine by the University of Granada of Rubén Martos Fernández. On a personal basis, the authors would like to acknowledge the strong positive influence Prof. Lotfi A. Zadeh has played on their research careers. They are very proud of having met and learned from Lotfi in different occassions, especially at the European Centre for Soft Computing and during the research stays some of the authors carried out in the BISC lab at Berkeley.
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Ibáñez, O. et al. (2021). Forensic Identification by Craniofacial Superimposition Using Fuzzy Set Theory. In: Lesot, MJ., Marsala, C. (eds) Fuzzy Approaches for Soft Computing and Approximate Reasoning: Theories and Applications. Studies in Fuzziness and Soft Computing, vol 394. Springer, Cham. https://doi.org/10.1007/978-3-030-54341-9_20
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