Comparison of AESA and LAESA search algorithms using string and tree-edit-distances

Pattern Recognition Letters

Volumn 24, Issue 9-10, 2003, Pages 1417-1426

  Rico Juan, Juan Ramón ^a   Micó, Luisa ^a  

^a UNIVERSITY OF ALICANTE   (Spain)

Author keywords

Edit distance; Handwritten character recognition; Metric spaces; Nearest neighbour; Pattern recognition

Indexed keywords

ALGORITHMS; MATRIX ALGEBRA;

METRIC SPACES;

CHARACTER RECOGNITION;

PATTERN RECOGNITION;

EID: 0037410697     PISSN: 01678655     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0167-8655(02)00382-3     Document Type: Article

References (18)

1. Carrasco, R. C., Forcada, M. L. 1995. A note on the Nagendraprasad-Wang-Gupta thinning algorithm. Pattern Recognition Lett. 16, 539-541.
2. Duda, R. O., Hart, P. E. 1973. Pattern Recognition and Scene Analysis. John Wiley and Sons, New York.
3. Freeman, H. 1961. On the encoding of arbitrary geometric configurations. IRE Trans. Electron. Comput., 10 260-268.
4. Gómez, E., Micó, L., Oncina, J., 1995. Testing the linear approximating eliminating search algorithm in handwritten character recognition tasks. In: Actas del VI Simposium Nacional de Reconocimiento de Formas y Análisis de Imágenes. Córdoba, Spain, pp. 212-217
5. Juan, A., Vidal, E., 2000. On the use of edit distances and an efficient k-NN search technique (k-AESA) for fast and accurate string classification. In: Proc. of the 15th Internat. Conf. Pattern Recognition (ICPR 2000), Spain, Vol. 2. pp. 680-683
6. López, D., Piñaga, I., 2000. Syntactic pattern recognition by error correcting analysis on tree automata. In: Ferri, F.J., Iñesta, J.M., Amin, A., Pudil, P. (Eds.), Advances in Pattern Recognition. Lecture Notes in Computer Science, Vol. 1876. Springer-Verlag, Berlin, pp. 133-142
7. Masek, W.J., Paterson, M.S. 1980. A faster algorithm for computing string edit distances. J. Comput. System Sci. 20, 18-31.
8. Micó, L., 1996. Algoritmos de búsqueda de vecinos más próximos en espacios métricos Ph.D. thesis, Universidad Universidad Computación.
9. Micó, L., & Oncina, J. 1998. Comparison of fast nearest neighbour classifiers for handwritten character recognition. Pattern Recognition Lett. 19, 351-356.
10. Mico, L., Oncina, J., Vidal, E. 1994. A new version of the nearest-neighbour approximating and eliminating search algorithm with linear preprocessing-time and memory requirements. Pattern Recognition Lett. 15, 9-17.
11. Rico-Juan, J.R., 1999. Off-line cursive handwritten word recognition based on tree extraction and an optimized classification distance. In: Torres, M.I., Sanfeliu, A. (Eds.), Pattern Recognition and Image Analysis: Proc. VII Symp. Nacional de Reconocimiento de Formas y Análisis de Imágenes, Bilbao, Spain, Vol. 3, pp. 15-16
12. Rico-Juan, J.R., Calera-Rubio, J., 2002. Evaluation of handwritten character recognizers using tree-edit-distance and fast nearest neighbour search. In: Iñesta, J.M., Micó, L. (Eds.), Pattern Recognition in Inform. Systems, Alicante, Spain. ICEIS PRESS, pp. 326-335.
13. Vidal, E. 1994. New formulation and improvements of the nearest-neighbour approximating and eliminating search algorithm (AESA). Pattern Recognition Lett., 15(1), 1-7.
14. Vidal, E., Casacuberta, F., Rulot, H. 1985. Is the DTW distance really a metric? An algorithm reducing the number of dtw comparisons in isolated words. Speech Comm. 4, 333-344.
15. Vidal, E., & Lloret, M. J. 1988. Fast speaker independent DTW recognition of isolated words using a metric-space search algorithm (AESA). Speech Comm. 7, 417-422.
16. Vidal, E., Rulot, H., Casacuberta, F., Benedí, J. 1988. On the use of a metric-space search algorithm (AESA) for fast DTW-bassed recognition of isolated words. IEEE Trans. Acoust., Speech, Signal Process., 36 651-660.
17. Wagner, R. A., Fischer, M. J. 1974. The string-to-string correction problem. J. ACM, 21 168-173.
18. Zhang, K., Shasha, D. 1989. Simple fast algorithms for the editing distance between trees and related problems. SIAM J. Comput. 18, 1245-1262.