A thresholding scheme of eliminating false detections on vehicles in wide-area aerial imagery
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IJSISE211488_April2018.pdf
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Final Accepted Manuscript
Author
Gao, XinAffiliation
Univ Arizona, Dept Elect & Comp EngnIssue Date
2018
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INDERSCIENCE ENTERPRISES LTDCitation
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.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 2018ISSN
1748-06981748-0701
Version
Final accepted manuscriptAdditional Links
http://www.inderscience.com/link.php?id=93827ae974a485f413a2113503eed53cd6c53
10.1504/IJSISE.2018.093827