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  • A brief review of document image retrieval methods: Recent advances

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    AlaeiPUB1936.pdf (149.3Kb)
    Author(s)
    Alaei, Fahimeh
    Alaei, Alireza
    Blumenstein, Michael
    Pal, Umapada
    Griffith University Author(s)
    Blumenstein, Michael M.
    Alaei, Ali Reza R.
    Alaei, Fahimeh
    Year published
    2016
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    Abstract
    Due to the rapid increase of different digitized documents, the development of a system to automatically retrieve document images from a large collection of structured and unstructured document images is in high demand. Many techniques have been developed to provide an efficient and effective way for retrieving and organizing these document images in the literature. This paper provides an overview of the methods which have been applied for document image retrieval over recent years. It has been found that from a textual perspective, more attention has been paid to the feature extraction methods without using OCR.Due to the rapid increase of different digitized documents, the development of a system to automatically retrieve document images from a large collection of structured and unstructured document images is in high demand. Many techniques have been developed to provide an efficient and effective way for retrieving and organizing these document images in the literature. This paper provides an overview of the methods which have been applied for document image retrieval over recent years. It has been found that from a textual perspective, more attention has been paid to the feature extraction methods without using OCR.
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    Conference Title
    2016 INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS (IJCNN)
    DOI
    https://doi.org/10.1109/IJCNN.2016.7727648
    Copyright Statement
    © 2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
    Subject
    Artificial Intelligence and Image Processing not elsewhere classified
    Publication URI
    http://hdl.handle.net/10072/339090
    Collection
    • Conference outputs

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