A New Editing Scheme Based on a Fast Two-String Median Computation Applied to OCR
This paper presents a new fast algorithm to compute an approximation to the median between two strings of characters representing a 2D shape and its application to a new classification scheme to decrease its error rate. The median string results from the application of certain edit operations from the minimum cost edit sequence to one of the original strings. The new dataset editing scheme relaxes the criterion to delete instances proposed by the Wilson Editing Procedure. In practice, not all instances misclassified by its near neighbors are pruned. Instead, an artificial instance is added to the dataset expecting to successfully classify the instance on the future. The new artificial instance is the median from the misclassified sample and its same-class nearest neighbor. The experiments over two widely used datasets of handwritten characters show this preprocessing scheme can reduce the classification error in about 78% of trials.
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- 1.Cárdenas, R.: A Learning Model for Multiple-Prototype Classification of Strings. In: 17th International Conference on Pattern Recognition, vol. 4, pp. 420–442 (2004)Google Scholar
- 2.Devijver, I., Kittler, J.: On the edited nearest neighbour rule. In: 5th Int. Conf. on Pattern Recognition, pp. 72–80 (1980)Google Scholar
- 4.Ferri, F., Vidal, E.: Comparison of several editing and condensing techniques for colour image segmentation and object location. Pattern Recognition and Image Analysis (1992)Google Scholar
- 5.Jiang, X., Schiffmann, L., Bunke, H.: Computation of median shapes. In: 4th Asian Conference on Computer Vision (2000)Google Scholar
- 9.Olvera, J., Martínez, F.: Edition schemes based on BSE. In: 10th Iberoamerican Congress on Pattern Recognition, pp. 360–368 (2005)Google Scholar
- 12.Sánchez, J., Pla, F., Ferri, F.: Using the nearest centroid neighbourhood concept for editing purposes. In: 7th Symposium National de Reconocimiento de Formas y Análisis de Imágen, vol. 1, pp. 175–180 (1997)Google Scholar
- 15.Vázquez, F., Sánchez, J., Pla, F.: A stochastic approach to Wilson’s editing algorithm. In: Marques, J.S., Pérez de la Blanca, N., Pina, P. (eds.) IbPRIA 2005. LNCS, vol. 3523, pp. 35–42. Springer, Heidelberg (2005)Google Scholar