## 3 Forensic Human Identification through the Analysis of Biomedical Images
### AI-Based Approaches for Craniofacial Superimposition
#### 3.4.1 Acquisition and Processing of the Materials  
The computerized systems developed for the first stage of CFS are related to face enhancement and skull modelling procedures. Skull 2D images, skull live images (video superimposition), and more frequently nowadays skull 3D models can be used in CFS. With the use of scanning devices, like laser range scanners, the forensic anthropologist can get a skull 3D model with a precision lower than one millimetre in a reasonable time [187]. The use of a 3D model instead of a 2D image is recommended, because it is a more accurate representation of the real skull. Since the first proposal to use a skull 3D model to tackle the CFS problem [166], 3D image reconstruction software is necessary to construct the 3D model by aligning the views in a common coordinate frame. Such image registration process consists of finding the best 3D rigid transformation (composed of a rotation and a translation) to align the acquired views of the object. In this sense, a method [170; 171] was proposed based on evolutionary algorithms for the automatic alignment of skull range images. Different views of the skull to be modeled were acquired by using a laser range scanner, and a two-step pair-wise range image registration technique was successfully applied to such images. The method is able to reconstruct the skull 3D model even if there is no turntable and the views are wrongly scanned. Today's technology, i.e., current 3D acquisition devices and corresponding software, automatically solve the alignment of the different acquisition views without the necessity of turn-tables o any additional device. \begin{table}
\begin{tabular}{l c c c} \hline \hline  & **APM** & **SFO** & **ADM** & **Remarks** \\ \hline [PERSON] et al., 1991 [166] & & ✓ & 3D-2D Image Registration (IR), \\  & & & binary-coded genetic algorithm \\ [PERSON] et al., 1995 and 1997 [167; 168] & & ✓ & Contour comparison using \\  & & & Fourier descriptors \\ [PERSON] and [PERSON], 2001 [169] & & ✓ & 2D-2D IR using Artificial Neural Network \\ [PERSON] et al., 2007 and 2009 [170; 171] & ✓ & & 3D skull model reconstruction \\  & & & using evolutionary algorithms \\ [PERSON] et al., 2009 [172] & ✓ & & 3D skull model reconstruction \\  & & & using heuristic features \\ [PERSON] et al., 2009 [173] & & ✓ & 3D-2D IR, \\  & & & real-coded evolutionary algorithm \\ [PERSON] et al., 2011 [174] & & ✓ & 3D-2D IR, 2D fuzzy landmark location \\ [PERSON] et al., 2013 [175] & ✓ & & 3D skull model simplification using \\  & & & multi-objective evolutionary algorithms \\ [PERSON] et al., 2014 [176] & & ✓ & 3D-3D morphology correlation \\  & & & using canonical analysis \\ [PERSON] et al., 2015 [177] & & ✓ & 3D-2D IR, fuzzy modeling \\  & & & of soft tissue [PERSON] \\ [PERSON] et al., 2016 [178] & & ✓ & SPO assessment using CV methods \\ [PERSON] et al., 2017 [179] & & ✓ & 3D-2D IR, mandible articulation \\  & & & using evolutionary algorithms \\ [PERSON] et al., 2017 and 2018 [180; 181] & ✓ & ✓ & 2D-2D Shared Transform Model for \\  & & & learning \\ [PERSON] et al., 2018 [182; 183] & & ✓ & discriminative representations \\  & & & Hierarchical decision support system \\ [PERSON] et al., 2018 [184] & & ✓ & 3D-2D IR, state-of-the-art SFO method \\ [PERSON] et al., 2019 [185] & ✓ & & 2D cephalometric landmark location \\  & & & using ML \\ [PERSON] et al., 2019 [186] & & ✓ & 3D-3D IR and matching using \\  & & & analytical curvature B-spline \\ \hline \hline \end{tabular}
\end{table} 
Table 3: An overview of the literature on AI-based approaches to the CFS problem. The stage of the process, i.e., Acquisition and Processing of the Materials (APM), skull-face overlay (SFO) and SFO assessment and decision making (ADM), that is addressed using an AI method is indicated with a ✓. Finally, a different related task was presented in [175]. The authors proposed a new algorithm to deal with the 3D open model mesh simplification problem from an evolutionary multi-objective point of view. An open model refers to a surface with open ends.