eprintid: 3996
rev_number: 18
eprint_status: archive
userid: 419
dir: disk0/00/00/39/96
datestamp: 2020-07-10 05:37:09
lastmod: 2020-07-10 09:17:18
status_changed: 2020-07-10 05:39:34
type: conference_item
metadata_visibility: show
creators_name: Tran, Xuan Tuyen
creators_name: Dinh, Tran Hiep
creators_name: Le, Vu Ha
creators_name: Zhu, Qiuchen
creators_name: Ha, Quang
creators_id: xuantuyen2901@gmail.com
creators_id: tranhiep.dinh@vnu.edu.vn
creators_id: halv@vnu.edu.vn
creators_id: Qiuchen.Zhu@student.uts.edu.au
creators_id: quang.ha@uts.edu.au
title: Defect detection based on singular value decomposition and
histogram thresholding
ispublished: inpress
subjects: ECE
subjects: ElectronicsandComputerEngineering
subjects: IT
divisions: avitech
divisions: fac_fet
divisions: fac_fema
abstract: This paper presents a novel method for defect
detection based on singular value decomposition (SVD) and
histogram thresholding. First, the input image is divided
into blocks, where SVD is applied to determine if a
region contains crack pixels. The detected crack blocks
are then merged to construct a histogram to calculate
the best binarization threshold by incoporating a recent
technique for multiple peaks detection and Otsu algorithm.
To validate the effectiveness and advantage of the
proposed approach over related thresholding algorithms,
experiments on images collected by an unmanned aerial
vehicle have been conducted for surface crack detection.
The obtained results have confirmed the merits of the
proposed approach in terms of accuracy when using some
well-known evaluation metrics.
date: 2020-07
date_type: published
full_text_status: public
pres_type: paper
event_title: The 2020 IEEE/ASME International Conference on Advanced Intelligent Mechatronics (AIM 2020)
event_type: conference
refereed: TRUE
citation:   Tran, Xuan Tuyen and Dinh, Tran Hiep and Le, Vu Ha and Zhu, Qiuchen and Ha, Quang  (2020) Defect detection based on singular value decomposition and histogram thresholding.  In: The 2020 IEEE/ASME International Conference on Advanced Intelligent Mechatronics (AIM 2020).    (In Press)  
document_url: https://eprints.uet.vnu.edu.vn/eprints/id/eprint/3996/1/SVD_6pR_AIMtemplate.pdf