dc.contributor.authorHung, Tzu-Yi
dc.contributor.authorVaikundam, Sriram
dc.contributor.authorNatarajan, Vidhya
dc.contributor.authorChia, Liang-Tien
dc.identifier.citationHung, T.-Y., Vaikundam, S., Natarajan, V., & Chia, L.-T. (2017). Phase Fourier Reconstruction for Anomaly Detection on Metal Surface Using Salient Irregularity. 23rd International Conference on Multimedia Modeling (MMM 2017), 290-302.en_US
dc.description12 p.
dc.description.abstractIn this paper, we propose a Phase Fourier Reconstruction (PFR) approach for anomaly detection on metal surfaces using salient irregularities. To get salient irregularity with images captured from an automatic visual inspection (AVI) system using different lighting settings, we first trained a classifier for image selection as only dark images are utilized for anomaly detection. By doing so, surface details, part design, and boundaries between foreground/background become indistinct, but anomaly regions are highlighted because of diffuse reflection caused by rough surfaces. Then PFR is applied so that regular patterns and homogeneous regions are further de-emphasized, and simultaneously, anomaly areas are distinct and located. Different from existing phase-based methods which require substantial texture information, our PFR works on both textual and non-textual images. Unlike existing template matching methods which require prior knowledge of defect-free patterns, our PFR is an unsupervised approach which detects anomalies using a single image. Experimental results on anomaly detection clearly demonstrate the effectiveness of the proposed method which outperforms several well-designed methods with a running time of less than 0.01 seconds per image.en_US
dc.description.sponsorshipNRF (Natl Research Foundation, S’pore)en_US
dc.rights© 2017 Springer International Publishing AG. This is the author created version of a work that has been peer reviewed and accepted for publication by 23rd International Conference on Multimedia Modeling (MMM 2017), Springer International Publishing AG. It incorporates referee’s comments but changes resulting from the publishing process, such as copyediting, structural formatting, may not be reflected in this document. The published version is available at: [http://dx.doi.org/10.1007/978-3-319-51811-4_24].en_US
dc.subjectAnomaly detectionen_US
dc.subjectDefect detectionen_US
dc.titlePhase Fourier Reconstruction for Anomaly Detection on Metal Surface Using Salient Irregularityen_US
dc.typeConference Paper
dc.contributor.conference23rd International Conference on Multimedia Modeling (MMM 2017)en_US
dc.contributor.researchRolls-Royce@NTU Corporate Laben_US
dc.contributor.schoolSchool of Computer Science and Engineeringen_US
dc.description.versionAccepted Version

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