Detail of Publication
| Text Language | Japanese |
|---|---|
| Authors | Seiichi Uchida, Megumi Sakai, Masakazu Iwamura, Shinichiro Omachi, and Koichi Kise |
| Title | Document Skew Estimation by Instance-Based Learning |
| Journal | Trans. IEICE |
| Vol. | J91-D |
| No. | 1 |
| Pages | pp.136-138 |
| Reviewed or not | Reviewed |
| Month & Year | January 2008 |
| Abstract | A novel document skew (i.e., rotation) estimation technique proposed in this paper has two properties: First, it estimates the rotation angle at each connected component. The entire rotation angle is determined by voting all the estimated rotation angles. Second, it employs instance-based learning where the rotation angle is estimated by referring stored instances each of which consists of a rotation invariant and a rotation variant. The result of a skew estimation experiment on 55 document images has shown that the skew angles of 54 document images were successfully estimated with errors smaller than 2.0 degrees. |
| URL | http://search.ieice.org/bin/summary.php?id=j91-d_1_136 |
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- Entry for BibTeX
@Article{Uchida2008, author = {Seiichi Uchida and Megumi Sakai and Masakazu Iwamura and Shinichiro Omachi and Koichi Kise}, title = {Document Skew Estimation by Instance-Based Learning}, journal = {Trans. IEICE}, year = 2008, month = jan, volume = {J91-D}, number = {1}, pages = {136--138}, URL = {http://search.ieice.org/bin/summary.php?id=j91-d_1_136} }