Computer-aided superimposition via reconstructing and matching 3D faces to 3D skulls for forensic craniofacial identifications

  • Joi San TanEmail author
  • Iman Yi Liao
  • Ibrahim Venkat
  • Bahari Belaton
  • P. T. Jayaprakash
Original Article


Identification of human remains via craniofacial superimposition (CS) is one of the prominent research areas in the forensic sciences. CS makes use of imaging techniques to identify an unknown skull by matching it with the available face photographs of missing individuals. Life-size enlargement of the face image and orientating the skull to correspond to the posture seen in the face photograph are the two main problems that affect identification accuracy with both the conventional and the computer-aided methods. Unlike the existing techniques, this research proposes a 3D skull–3D face model superimposition (3D–3D) approach to address the above two issues. The proposed method commences by reconstructing the 3D face model from a given 2D face image using the mean simplified generic elastic model, followed by registering the face model to a 3D skull along the jaw line using the analytical curvature B-spline (AC B-spline). The accuracy index of the registration is then evaluated to suggest the degree to which the face image corresponds to a skull. The superimpositions of positive and negative cases were conducted on a set of 3D skulls versus a set of 2D face images. The accuracy indices of the registration results suggest that the AC B-spline is more robust in 3D–3D superimposition compared to the other existing methods. The full experimental results have demonstrated the potential of the proposed method as an assistive tool to the forensic scientists for craniofacial identifications.


Craniofacial superimposition 3D face reconstruction Generic elastic model Curve registration B-spline 



This research is supported by Department of Radiology Hospital Universiti Sains Malaysia (RUT Grant, 1001/PPSG/852004).

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

Ethical standards

CT head scans of patients were randomly collected from the picture archiving and communication system (PACS) server at the Radiology Department, Hospital USM. They were scanned using the Siemens Somatom Definition AS+ 128-slice (Siemens Medical Solutions, Erlangen, Germany). Ethical application was approved by the Ethics and Research Committee USM, reference number USMKK/PPP/JEPeM (246.3[13]). Part of the collected data were also approved by the Research Ethics Committee The National University of Malaysia (UKM PPI/111/8/JEP-2016-100). Besides, this research was supported by the ScienceFund Malaysia (01-01-05-SF0045) and RUI Grant of Universiti Sains Malaysia (1001/PKOMP/814109).


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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Department of Computer ScienceUniversiti Tunku Abdul RahmanKamparMalaysia
  2. 2.School of Computer ScienceThe University of Nottingham Malaysia CampusSemenyihMalaysia
  3. 3.School of Computing and InformaticsUniversiti Teknologi BruneiBandar Seri BegawanBrunei
  4. 4.School of Computer SciencesUniversiti Sains MalaysiaGelugorMalaysia
  5. 5.Forensic ScienceprogramUniversiti Sains MalaysiaKubang KerianMalaysia

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