relation: https://eprints.uet.vnu.edu.vn/eprints/id/eprint/3996/
title: Defect detection based on singular value decomposition and  histogram thresholding
creator: Tran, Xuan Tuyen
creator: Dinh, Tran Hiep
creator: Le, Vu Ha
creator: Zhu, Qiuchen
creator: Ha, Quang
subject: Electronics and Communications
subject: Electronics and Computer Engineering
subject: Information Technology (IT)
description: 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
type: Conference or Workshop Item
type: PeerReviewed
format: application/pdf
language: en
identifier: https://eprints.uet.vnu.edu.vn/eprints/id/eprint/3996/1/SVD_6pR_AIMtemplate.pdf
identifier:   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)