Japanese / English

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.
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