Artículo

Romero, D.; Ruedin, A.; Seijas, L. "Wavelet-based feature extraction for handwritten numerals" (2009) 15th International Conference on Image Analysis and Processing - ICIAP 2009, Proceedings. 5716 LNCS:374-383
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Abstract:

We present a novel preprocessing technique for handwritten numerals recognition, that relies on the extraction of multiscale features to characterize the classes. These features are obtained by means of different continuous wavelet transforms, which behave as scale-dependent bandpass filters, and give information on local orientation of the strokes. First a shape-preserving, smooth and smaller version of the digit is extracted. Second, a complementary feature vector is constructed, that captures certain properties of the digits, such as orientation, gradients and curvature at different scales. The accuracy with which the selected features describe the original digits is assessed with a neural network classifier of the multilayer perceptron (MLP) type. The proposed method gives satisfactory results, regarding the dimensionality reduction as well as the recognition rates on the testing sets of CENPARMI and MNIST databases; the recognition rate being 92.60 % for the CENPARMI data-base and 98.22 % for the MNIST database. © 2009 Springer Berlin Heidelberg.

Registro:

Documento: Artículo
Título:Wavelet-based feature extraction for handwritten numerals
Autor:Romero, D.; Ruedin, A.; Seijas, L.
Ciudad:Vietri sul Mare
Filiación:Departamento de Computació, Facultad de Ciencias Exactas y Naturales, Ciudad Universitaria, Buenos Aires C1428EGA, Argentina
Palabras clave:Continuous Wavelet Transform; Dimensionality Reduction; Handwritten Numerals; Pattern Recognition; Complementary features; Continuous Wavelet Transform; Different scale; Dimensionality reduction; Handwritten numeral; Handwritten Numerals; Local orientations; Multi layer perceptron; Multi-scale features; Neural network classifier; Preprocessing techniques; Recognition rates; Shape-preserving; Testing sets; Wavelet-based Feature; Bandpass filters; Character recognition; Feature extraction; Image analysis; Neural networks; Wavelet transforms
Año:2009
Volumen:5716 LNCS
Página de inicio:374
Página de fin:383
DOI: http://dx.doi.org/10.1007/978-3-642-04146-4_41
Título revista:15th International Conference on Image Analysis and Processing - ICIAP 2009, Proceedings
Título revista abreviado:Lect. Notes Comput. Sci.
ISSN:03029743
Registro:https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_03029743_v5716LNCS_n_p374_Romero

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Citas:

---------- APA ----------
Romero, D., Ruedin, A. & Seijas, L. (2009) . Wavelet-based feature extraction for handwritten numerals. 15th International Conference on Image Analysis and Processing - ICIAP 2009, Proceedings, 5716 LNCS, 374-383.
http://dx.doi.org/10.1007/978-3-642-04146-4_41
---------- CHICAGO ----------
Romero, D., Ruedin, A., Seijas, L. "Wavelet-based feature extraction for handwritten numerals" . 15th International Conference on Image Analysis and Processing - ICIAP 2009, Proceedings 5716 LNCS (2009) : 374-383.
http://dx.doi.org/10.1007/978-3-642-04146-4_41
---------- MLA ----------
Romero, D., Ruedin, A., Seijas, L. "Wavelet-based feature extraction for handwritten numerals" . 15th International Conference on Image Analysis and Processing - ICIAP 2009, Proceedings, vol. 5716 LNCS, 2009, pp. 374-383.
http://dx.doi.org/10.1007/978-3-642-04146-4_41
---------- VANCOUVER ----------
Romero, D., Ruedin, A., Seijas, L. Wavelet-based feature extraction for handwritten numerals. Lect. Notes Comput. Sci. 2009;5716 LNCS:374-383.
http://dx.doi.org/10.1007/978-3-642-04146-4_41