文献の詳細
| 論文の言語 | 英語 |
|---|---|
| 著者 | Kazutaka Takeda, Koichi Kise, Masakazu Iwamura |
| 論文名 | Memory Reduction for Real-Time Document Image Retrieval with a 20 Million Pages Database |
| 論文誌名 | Proc. Fourth International Workshop on Camera-Based Document Analysis and Recognition (CBDAR2011) |
| ページ | pp.59-64 |
| 発表場所 | Beijing, China |
| 査読の有無 | 有 |
| 発表の種類 | 口頭発表 |
| 年月 | 2011年9月 |
| 要約 | 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. |
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- BibTeX用エントリー
@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} }