Detail of Publication
| Text Language | English |
|---|---|
| Authors | Kazutaka Takeda, Koichi Kise, Masakazu Iwamura |
| Title | Memory Reduction for Real-Time Document Image Retrieval with a 20 Million Pages Database |
| Journal | Proc. Fourth International Workshop on Camera-Based Document Analysis and Recognition (CBDAR2011) |
| Pages | pp.59-64 |
| Location | Beijing, China |
| Reviewed or not | Reviewed |
| Presentation type | Oral |
| Month & Year | September 2011 |
| Abstract | We have introduced the three improvements of Locally Likely Arrangement Hashing (LLAH) in ICDAR2011 to reduce a required amount of memory and increase discrimination power of features. In this paper, we show the experimental results which is obtained on a larger-scale database than that utilized for ICDAR2011. From experimental results, we have confirmed that the proposed method realizes 60% memory reduction and achieves 99.2% accuracy with 49ms/query processing time for the retrieval of a database of 20 million pages. |
- Following files are available.
- Entry for BibTeX
@InProceedings{Takeda2011, author = {Kazutaka Takeda and Koichi Kise and Masakazu Iwamura}, title = {Memory Reduction for Real-Time Document Image Retrieval with a 20 Million Pages Database}, booktitle = {Proc. Fourth International Workshop on Camera-Based Document Analysis and Recognition (CBDAR2011)}, year = 2011, month = sep, pages = {59--64}, location = {Beijing, China} }