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    A thresholding scheme of eliminating false detections on vehicles in wide-area aerial imagery

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    Name:
    IJSISE211488_April2018.pdf
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    Description:
    Final Accepted Manuscript
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    Author
    Gao, Xin
    Affiliation
    Univ Arizona, Dept Elect & Comp Engn
    Issue Date
    2018
    Keywords
    vehicle detection
    thresholding
    false positive
    wide-area aerial imagery
    
    Metadata
    Show full item record
    Publisher
    INDERSCIENCE ENTERPRISES LTD
    Citation
    Gao, X. (2018). A thresholding scheme of eliminating false detections on vehicles in wide-area aerial imagery. International Journal of Signal and Imaging Systems Engineering, 11(4), 217-224.
    Journal
    INTERNATIONAL JOURNAL OF SIGNAL AND IMAGING SYSTEMS ENGINEERING
    Rights
    Copyright © 201x Inderscience Enterprises Ltd.
    Collection Information
    This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at repository@u.library.arizona.edu.
    Abstract
    Post-processings are usually necessary to reduce false detections on vehicles in wide-area aerial imagery. In order to improve the performance of vehicle detection, we propose a two-stage scheme, which consists of a thresholding method by constructing a pixel-weight based thresholding policy to classify pixels in the greyscale feature map of an automatic detection algorithm followed by morphological filtering. We use two aerial videos for performance evaluation, and compare the automatic detection results with the ground-truth objects. We compute average F-score and percentage of wrong classifications towards six detection algorithms before and after applying the proposed scheme. We measure the variation of overlap ratios from detections to objects, and establish sensitivity analysis to evaluate the performance of proposed scheme by combining it on each of two representative algorithms. Simulation results verify both validity and efficiency of the proposed thresholding scheme, also display the difference of detection performance between datasets and among algorithms.
    Note
    12 month embargo; available online: 27 Jul 2018
    ISSN
    1748-0698
    1748-0701
    DOI
    10.1504/IJSISE.2018.093827
    Version
    Final accepted manuscript
    Additional Links
    http://www.inderscience.com/link.php?id=93827
    ae974a485f413a2113503eed53cd6c53
    10.1504/IJSISE.2018.093827
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    UA Faculty Publications

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