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A classification of discrete contours via signatures is studied. Two algorithms to compute the signature have been developed. In the first algorithm a multidimensional sorting is used. The second algorithm is based on a simple geometrical considerations. Two types of signature are considered — the length signature and the area signature. Statistical features based on Fourier descriptors are derived from the signatures. In classification the k-NN algorithm is used with k and the size of the feature vector chosen experimentally. The algorithms have been tested on the handwritten, totally unconstrained characters from Suen’s data base and recognition success rates of 91% and 93% were achieved for the length and area signature respectively…