Detail of Publication
Text Language | English |
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Authors | Tomohiro Nakai, Koichi Kise, Masakazu Iwamura |
Title | 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— |
Journal | Proc. First International Workshop on Camera-Based Document Analysis and Recognition (CBDAR2005) |
Pages | pp.87-94 |
Location | Seoul, South Korea |
Reviewed or not | Reviewed |
Month & Year | August 2005 |
Abstract | 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). |
- Following file is available.
- Entry for BibTeX
@InProceedings{Nakai2005, author = {Tomohiro Nakai and Koichi Kise and Masakazu Iwamura}, title = {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\—}, booktitle = {Proc. First International Workshop on Camera-Based Document Analysis and Recognition (CBDAR2005)}, year = 2005, month = aug, pages = {87--94}, location = {Seoul, South Korea} }