Japanese / English


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
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.