Please use this identifier to cite or link to this item: http://hdl.handle.net/2440/116699
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Type: Journal article
Title: Improving Chamfer template matching using image segmentation
Author: Nguyen, D.
Vu, N.
Do, T.
Nguyen, T.
Yearwood, J.
Citation: IEEE Signal Processing Letters, 2018; 25(11):1635-1639
Publisher: IEEE
Issue Date: 2018
ISSN: 1070-9908
1558-2361
Statement of
Responsibility: 
Duc Thanh Nguyen, Ngoc-Son Vu, Thanh-Toan Do, Thin Nguyen and John Yearwood
Abstract: This letter proposes an effective method to improve object location in Chamfer template matching (CTM) based object detection using image segmentation. In our method, object bounding boxes are iteratively adjusted to fit with the object images obtained from image segmentation in a probabilistic model. The proposed method was tested with state-of-the-art CTM-based object detectors. Experimental results have shown the proposed method improved the location accuracy of the object detectors and reduce the false alarms rate.
Keywords: Chamfer template matching (CTM); image segmentation; object detection
Rights: © 2018 IEEE. Personal use is permitted, but republication/redistribution requires IEEE permission. See http://www.ieee.org/publications standards/publications/rights/index.html for more information.
RMID: 0030095806
DOI: 10.1109/LSP.2018.2862645
Appears in Collections:Aurora submissions

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