Identification of actors drawn in Ukiyoe pictures

Abstract This paper presents the development of line image keywords for the identification of actors drawn in Japanese traditional painting pictures known as Ukiyoe pictures. The system is based on visual features of the face from the image database files and is organized as a set of classifiers whose outputs are integrated after a normalization step. Line profile from the picture has been extracted in this investigation and has been approximated by Bezier curves. A learning algorithm has been developed to obtain the control points at high accuracy. A new curve matching method has been developed based on the feature points, rather than the corresponding points. This method can automatically fit a set of data points with piecewise geometrically continuous third order Bezier curves. Last of all, a new approach for distance calculation, namely “apple-node distance” has been introduced here for similarity calculation in image retrieval systems. The computation of similarity between curves has been established on the basis of this “apple-node” distance. The effectiveness of our method has been confirmed through computer simulation. The method developed here can be expanded to one of three dimensional shape-analyzing tools.