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Expansion of queries and databases for improving the retrieval accuracy of document portions: an application to a camera-pen system

Published: 09 June 2010 Publication History

Abstract

This paper presents a method of improving the accuracy of document image retrieval focusing on the application to a camera-pen system. In a camera-pen system, document image retrieval is employed for locating the pen-tip position on a page. A serious problem is that since the camera is mounted close to the pen-tip, the camera captures only a tiny portion of the page and the resultant image is under severe perspective distortion, resulting in lowering the retrieval accuracy. To solve this problem, we propose new geometrically invariant features as well as expansion techniques which increase the number of index features of either the database or the query images. From the experimental results, it has been found that the query expansion technique with features by combining affine and perspective invariants allows us the best performance that improves the accuracy of a baseline method more than 27%.

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  • (2022)Online Handwriting Recognition Based on Microphone and IMU2022 IEEE 5th International Conference on Electronics Technology (ICET)10.1109/ICET55676.2022.9824489(1075-1079)Online publication date: 13-May-2022
  • (2019)A comparison of local features for camera-based document image retrieval and spottingInternational Journal on Document Analysis and Recognition (IJDAR)10.1007/s10032-019-00329-wOnline publication date: 12-Jul-2019
  • (2018)PentelligenceProceedings of the 2018 CHI Conference on Human Factors in Computing Systems10.1145/3173574.3173705(1-11)Online publication date: 21-Apr-2018
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  1. Expansion of queries and databases for improving the retrieval accuracy of document portions: an application to a camera-pen system

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    DAS '10: Proceedings of the 9th IAPR International Workshop on Document Analysis Systems
    June 2010
    490 pages
    ISBN:9781605587738
    DOI:10.1145/1815330
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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    Published: 09 June 2010

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    • (2022)Online Handwriting Recognition Based on Microphone and IMU2022 IEEE 5th International Conference on Electronics Technology (ICET)10.1109/ICET55676.2022.9824489(1075-1079)Online publication date: 13-May-2022
    • (2019)A comparison of local features for camera-based document image retrieval and spottingInternational Journal on Document Analysis and Recognition (IJDAR)10.1007/s10032-019-00329-wOnline publication date: 12-Jul-2019
    • (2018)PentelligenceProceedings of the 2018 CHI Conference on Human Factors in Computing Systems10.1145/3173574.3173705(1-11)Online publication date: 21-Apr-2018
    • (2017)A System for Camera-Based Retrieval of Heterogeneous-Content Complex Linguistic MapGraphic Recognition. Current Trends and Challenges10.1007/978-3-319-52159-6_7(86-99)Online publication date: 8-Jan-2017
    • (2016)Camera-based document image spotting system for complex linguistic maps2016 IEEE International Conference on Systems, Man, and Cybernetics (SMC)10.1109/SMC.2016.7844734(003246-003251)Online publication date: Oct-2016
    • (2016)Polygon-shape-based Scale and Rotation Invariant Features for camera-based document image retrieval2016 23rd International Conference on Pattern Recognition (ICPR)10.1109/ICPR.2016.7900001(2434-2439)Online publication date: Dec-2016
    • (2016)Delaunay Triangulation-Based Features for Camera-Based Document Image Retrieval System2016 12th IAPR Workshop on Document Analysis Systems (DAS)10.1109/DAS.2016.66(1-6)Online publication date: Apr-2016
    • (2015)SRIFProceedings of the 2015 13th International Conference on Document Analysis and Recognition (ICDAR)10.1109/ICDAR.2015.7333832(601-605)Online publication date: 23-Aug-2015
    • (2012)Gaze guided object recognition using a head-mounted eye trackerProceedings of the Symposium on Eye Tracking Research and Applications10.1145/2168556.2168570(91-98)Online publication date: 28-Mar-2012
    • (2011)Real-Time Document Image Retrieval for a 10 Million Pages Database with a Memory Efficient and Stability Improved LLAHProceedings of the 2011 International Conference on Document Analysis and Recognition10.1109/ICDAR.2011.213(1054-1058)Online publication date: 18-Sep-2011
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