Contour Regularity Extraction Based on String Edit Distance

In this paper, we present a new method for constructing prototypes representing a set of contours encoded by Freeman Chain Codes. Our method build new prototypes taking into account similar segments shared between contours instances. The similarity criterion was based on the Levenshtein Edit Distance definition. We also outline how to apply our method to reduce a data set without sensibly affect its representational power for classification purposes. Experimental results shows that our scheme can achieve compressions about 50% while classification error increases only by 0.75%.