Abstract
An algorithm for automatic image-map alignment problem using a new similarity measure named Edge-Based Code Mutual Information (EBCMI) and Hilbert scan is presented in this study. Because image and map are very different in their representations, the normal Mutual Information (MI) using the intensity in traditional alignment method may result in misalignment. To solve the problem, codes which are robust to the differences between the image-map pairs are constructed and Mutual Information of the codes is computed as the similarity measure for the alignment. We convert the 3-D transformation search space in alignment to a 1-D search space sequence by using 3-D Hilbert Scan. A new search strategy is also proposed on the 1-D search space sequence. The experimental results show that the proposed EBCMI outperformed the normal MI and some other similarity measures and the proposed search strategy gives flexibility between efficiency and accuracy for automatic imagemap alignment task.
| Original language | English |
|---|---|
| Title of host publication | European Signal Processing Conference |
| Publication status | Published - 2008 |
| Event | 16th European Signal Processing Conference, EUSIPCO 2008 - Lausanne, Switzerland Duration: 2008 Aug 25 → 2008 Aug 29 |
Other
| Other | 16th European Signal Processing Conference, EUSIPCO 2008 |
|---|---|
| Country | Switzerland |
| City | Lausanne |
| Period | 08/8/25 → 08/8/29 |
ASJC Scopus subject areas
- Signal Processing
- Electrical and Electronic Engineering
Cite this
An automatic image-map alignment algorithm based on Mutual Information and Hilbert scan. / Tian, Li; Kamata, Seiichiro.
European Signal Processing Conference. 2008.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - An automatic image-map alignment algorithm based on Mutual Information and Hilbert scan
AU - Tian, Li
AU - Kamata, Seiichiro
PY - 2008
Y1 - 2008
N2 - An algorithm for automatic image-map alignment problem using a new similarity measure named Edge-Based Code Mutual Information (EBCMI) and Hilbert scan is presented in this study. Because image and map are very different in their representations, the normal Mutual Information (MI) using the intensity in traditional alignment method may result in misalignment. To solve the problem, codes which are robust to the differences between the image-map pairs are constructed and Mutual Information of the codes is computed as the similarity measure for the alignment. We convert the 3-D transformation search space in alignment to a 1-D search space sequence by using 3-D Hilbert Scan. A new search strategy is also proposed on the 1-D search space sequence. The experimental results show that the proposed EBCMI outperformed the normal MI and some other similarity measures and the proposed search strategy gives flexibility between efficiency and accuracy for automatic imagemap alignment task.
AB - An algorithm for automatic image-map alignment problem using a new similarity measure named Edge-Based Code Mutual Information (EBCMI) and Hilbert scan is presented in this study. Because image and map are very different in their representations, the normal Mutual Information (MI) using the intensity in traditional alignment method may result in misalignment. To solve the problem, codes which are robust to the differences between the image-map pairs are constructed and Mutual Information of the codes is computed as the similarity measure for the alignment. We convert the 3-D transformation search space in alignment to a 1-D search space sequence by using 3-D Hilbert Scan. A new search strategy is also proposed on the 1-D search space sequence. The experimental results show that the proposed EBCMI outperformed the normal MI and some other similarity measures and the proposed search strategy gives flexibility between efficiency and accuracy for automatic imagemap alignment task.
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M3 - Conference contribution
AN - SCOPUS:84863734027
BT - European Signal Processing Conference
ER -