This study investigated the relationship between social skills and facial asymmetry in facial expressions. Three-dimensional facial landmark data of facial expressions (neutral, happy, and angry) were obtained from Japanese participants (n = 62). Following a facial expression task, each participant completed KiSS-18 (Kikuchi's Scale of Social Skills; Kikuchi, 2007). Using a generalized Procrustes analysis, faces and their mirror-reversed versions were represented as points on a hyperplane. The asymmetry of each individual face was defined as Euclidian distance between the face and its mirror reversed face on this plane. Subtraction of the asymmetry level of a neutral face of each individual from the asymmetry level of a target emotion face was defined as the index of “expression asymmetry” given by a particular emotion. Correlation coefficients of KiSS-18 scores and expression asymmetry scores were computed for both happy and angry expressions. Significant negative correlations between KiSS-18 scores and expression asymmetries were found for both expressions. Results indicate that the symmetry in facial expressions increases with higher level of social skills.

In this paper, a novel description method of the contour of a shape using extended fractal interpolation functions (EFIFs) is presented. Although the scope of application of traditional FIFs has been limited to cases in which a given signal is represented by a single-valued function, the EFIFs derived by the introduction of a new parameter can describe a multiple-valued signal such as the contour of a shape with a high level of accuracy. Furthermore, the proposed description method possesses the useful property that once a given contour has been modeled by the proposed description method, the shape can be easily expanded at an arbitrary expansion rate. Experimental results show the effectiveness and usefulness of the proposed description method for representing contours.

Mathematical morphology clarified geometrical properties of shape analysis algorithms for binary pictures. Results of labelling, distance transform, and adjacent numbering are, however, coded pictures. For full descriptions of shape analysis algorithms in the framework of mathematical morphology, it is necessary to extend morphological operations to code-labelled pictorial data. Nevertheless, extensions of morphology to code-labelled pictures have never discussed though the theory of gray morphology is well studied by several authors. Hence, this paper proposes a theory of the coded morphology which is based on the binary scaling of labels of pixels. The method uses n-layered binary sub-pictures for the processing of a picture with 2n labels. By introducing morphological operations for the coded point sets, we express some coding functions in the manner of the mathematical morphology. We also derive multidimensional array registers and gates which store and process coded pictures and morphological operations to them by proposing basic gates which compute parallelly logical operations for elements of Boolean layered arrays. These gates and registers are suitable for the implementation of the shape analysis processors on the three-dimensional VLSI and ULSI.