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Communication Dans Un Congrès Année : 2015

Camera-based document image retrieval system using local features - comparing SRIF with LLAH, SIFT, SURF and ORB

Résumé

—In this paper, we present camera-based document retrieval systems using various local features as well as various indexing methods. We employ our recently developed features, named Scale and Rotation Invariant Features (SRIF), which are computed based on geometrical constraints between pairs of nearest points around a keypoint. We compare SRIF with state-of-the-art local features. The experimental results show that SRIF outperforms the state-of-the-art in terms of retrieval time with 90.8% retrieval accuracy.
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Dates et versions

hal-01248152 , version 1 (23-12-2015)

Identifiants

Citer

Quoc Bao Dang, Viet Phuong Le, Muhammad Muzzamil Luqman, Mickaël Coustaty, De Cao Tran, et al.. Camera-based document image retrieval system using local features - comparing SRIF with LLAH, SIFT, SURF and ORB. International Conference on Document Analysis and Recognition, Aug 2015, Nancy, France. pp.1211-1215, ⟨10.1109/ICDAR.2015.7333956⟩. ⟨hal-01248152⟩

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