Abstract
Human beings are capable of distinguishing a variety of texture almost at a glance. By modelling the mechanism, we will realize a flexible texture analysis. We propose a new technique inspired by such human early-vision ability to distinguish handwritten character regions from machine-printed regions in document images. In the technique, we evaluate the two-dimensional power spectrum to extract feature values that reflects fluctuations unavoidable in handwritten characters. Experiments show that a certain feature value of handwritten characters is often larger than that of machine-printed characters. We generated a map obtained by superimposing the feature value on the document image. The map showed that our proposed method is useful to distinguish handwritten character regions from machine-printed character ones.
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Koyama, J., Kato, M., Hirose, A. (2008). Handwritten Character Distinction Method Inspired by Human Vision Mechanism. In: Ishikawa, M., Doya, K., Miyamoto, H., Yamakawa, T. (eds) Neural Information Processing. ICONIP 2007. Lecture Notes in Computer Science, vol 4984. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-69158-7_106
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DOI: https://doi.org/10.1007/978-3-540-69158-7_106
Publisher Name: Springer, Berlin, Heidelberg
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