Abstract
The normalization strategy is popularly used in character recognition to reduce the shape variation. This procedure, however, also gives rise to excessive shape distortion and eliminates some useful information. This paper proposes an aspect ratio adaptive normalization (ARAN) method to overcome the above problems and so as to improve the recognition performance. Experimental results of multilingual character recognition and numeral recognition demonstrate the advantage of ARAN over conventional normalization method.
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Liu, CL., Koga, M., Sako, H., Fujisawa, H. (2000). Aspect Ratio Adaptive Normalization for Handwritten Character Recognition. In: Tan, T., Shi, Y., Gao, W. (eds) Advances in Multimodal Interfaces — ICMI 2000. ICMI 2000. Lecture Notes in Computer Science, vol 1948. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-40063-X_55
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DOI: https://doi.org/10.1007/3-540-40063-X_55
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