The Continuos Distance Transformation: a Generalization of the Distance Transformation for Continuos-valued Images

A feature extraction method for images is presented. It is based on the classical concept of Distance Transformation (DT) from which we develop a generalization, the Continuos Distance Transformation (CDT). Whereas the DT can only be applied to binary images, the CDT can be applied to both binary and gray-scale or color pictures. Furthermore, we define a number of new metrics and dissimilarity measures based on the CDT. Comparative experimental results are also presented for the new measures, using the NIST’s handwritten characters database. Several experiments using the k nearest neighbor classification rule are presented which significatively improve the recognition rate of other measures like the Euclidean Distance or DT-based ones.