A comparison of local features for camera-based document image retrieval and spotting

Abstract

This paper aims at comparing robustness of local features for camera-based document image retrieval and spotting system. We present a literature review of the state of the art of local features extraction that includes keypoint detectors and keypoint descriptors. We also present a dataset and evaluation protocol for camera-based document image retrieval and spotting systems. This dataset is composed of three subparts: The first dataset represents the images with textual content only; the second dataset represents images with graphical content mainly; the third dataset contains text plus graphical elements. Along with the datasets, we present the protocol that describes measurements to evaluate the accuracy and processing time of camera-based document image retrieval and spotting systems. The latter is employed for presenting a detailed evaluation of local features from the literature.

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    http://www.ipevo.com/prods/ipevo-vz-1-hd-vga-usb-document-camera.

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    http://navidomass.univ-lr.fr/SRIFDataset/.

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Correspondence to Quoc Bao Dang.

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Dang, Q.B., Coustaty, M., Luqman, M.M. et al. A comparison of local features for camera-based document image retrieval and spotting. IJDAR 22, 247–263 (2019). https://doi.org/10.1007/s10032-019-00329-w

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Keywords

  • Camera-based document image analysis, recognition and retrieval
  • Keypoint detection
  • Keypoint extraction
  • Local feature
  • Document image analysis, recognition and understanding
  • Pattern recognition