Hashing with Local Combinations of Feature Points and Its Application to Camera-Based Document Image Retrieval—Retrieval in 0.14 Second from 10,000 Pages—
| 言語 | 英語 |
|---|---|
| 種類 | 国際会議等の予稿 |
| 著者 | Tomohiro Nakai，Koichi Kise，Masakazu Iwamura |
| 論文名 | Hashing with Local Combinations of Feature Points and Its Application to Camera-Based Document Image Retrieval—Retrieval in 0.14 Second from 10,000 Pages— |
| 論文誌名 | Proc. First International Workshop on Camera-Based Document Analysis and Recognition (CBDAR2005) |
| ページ | pp.87-94 |
| 発表場所 | Seoul, South Korea |
| 査読の有無 | 有 |
| 年月 | 2005年8月 |
| 分野 | 文書画像解析, 文書画像検索 |
| キー | Nakai2005_CBDAR (id=369) |
要約
This paper presents a new method of indexing and retrieval of planar objects based on feature points and its application to document image retrieval using cameras. As the indexing method we propose a method based on local combinations of projective invariants calculated from feature points. As the retrieval method we employ a voting technique for efficiency and robustness against erasure of feature points. Experimental results on 10,000 images with 50 queries show that the method is effective (98% accuracy; the remaining query was ranked at the 5th position among 10,000) and efficient (0.14 second per query).
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