Abstract
Gabor filter-based features are useful for handprinted character recognition. One needs to optimize Gabor filter parameters because the performance of Gabor features depends strongly on Gabor filter parameters. One way to find the optimal values of the parameters is to analyze statistically the influence of the parameters on the error rate. In this paper, we discuss a statistical analysis of Gabor parameters for handwritten numeral recognition by experimental design. Our statistical analysis shows that optimal values of standard deviations σx and σy in Gabor filter are functions of the wavelength of the filter. In addition, it is shown that optimal values of σx and σy can be separately set on the condition that σx > σy.
Chapter PDF
References
Gabor, D.: Theory of communication. J. Inst. Elect. Engr. 93 (1946) 429–457
Daugman, J.G.: Two-dimensional spectral analysis of cortical receptive field profiles. Vision Res. 20 (1980) 847–856
Marčelja, S.: Mathematical description of the responses of simple cortical cells. J. Opt. Soc. Am. 70 (1980) 1297–1300
Hamamoto, Y., et al: A Gabor filter-based method for recognizing handwritten numerals. Pattern Recognition 31 (1998) 395–400
Hamamoto, Y., et al: Recognition of handprinted Chinese characters using Gabor features. Proc. 3rd Int. Conf. Document Analysis and Recognition (1995) 819–823
Turner, M.R.: Texture discrimination by Gabor functions. Biol. Cybern. 55 (1986) 71–82
Lampinen, J., Oja, E.: Distortion tolerant pattern recognition based on selforganizing feature extraction. IEEE Trans. Neural Networks 6 (1995) 539–547
Yamada, K., Tsukumo, J.: Consideration on stability of Gabor feature extraction and character recognition application. Tech. Rep. IEICE Japan PRU92-112 (1993) 75–82 (in Japanese)
Jain, A.K., Bhattacharjee, S.K.: Address block location on envelopes using Gabor filters. Pattern Recognition 25 (1992) 1459–1477
Montgomery, D.C.: Design and Analysis of Experiment, 4th Edition. John Wiley and Sons (1997)
Yamamoto, K.: Present state of recognition method on consideration of neighbor points and its ability in common database. MICE Trans. Information and Systems E79-D (1996) 417–422
Fukunaga, K.: Introduction to Statistical Pattern Recognition, 2nd Edition. Academic Press (1990)
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 1998 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Uchimura, S., Mizuno, K., Hamamoto, Y., Tomita, S. (1998). Analysis of Gabor parameters for handwritten numeral recognition by experimental design. In: Amin, A., Dori, D., Pudil, P., Freeman, H. (eds) Advances in Pattern Recognition. SSPR /SPR 1998. Lecture Notes in Computer Science, vol 1451. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0033326
Download citation
DOI: https://doi.org/10.1007/BFb0033326
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-64858-1
Online ISBN: 978-3-540-68526-5
eBook Packages: Springer Book Archive