relation: https://khub.utp.edu.my/scholars/16415/
title: SpecSeg Network for Specular Highlight Detection and Segmentation in Real-World Images
creator: Anwer, A.
creator: Ainouz, S.
creator: Saad, M.N.M.
creator: Ali, S.S.A.
creator: Meriaudeau, F.
description: Specular highlights detection and removal in images is a fundamental yet non-trivial problem of interest. Most modern techniques proposed are inadequate at dealing with real-world images taken under uncontrolled conditions with the presence of complex textures, multiple objects, and bright colours, resulting in reduced accuracy and false positives. To detect specular pixels in a wide variety of real-world images independent of the number, colour, or type of illuminating source, we propose an efficient Specular Segmentation (SpecSeg) network based on the U-net architecture that is expeditious to train on nominal-sized datasets. The proposed network can detect pixels strongly affected by specular highlights with a high degree of precision, as shown by comparison with the state-of-the-art methods. The technique proposed is trained on publicly available datasets and tested using a large selection of real-world images with highly encouraging results. © 2022 by the authors.
publisher: MDPI
date: 2022
type: Article
type: PeerReviewed
identifier:   Anwer, A. and Ainouz, S. and Saad, M.N.M. and Ali, S.S.A. and Meriaudeau, F.  (2022) SpecSeg Network for Specular Highlight Detection and Segmentation in Real-World Images.  Sensors, 22 (17).   ISSN 14248220     
relation: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85137597770&doi=10.3390%2fs22176552&partnerID=40&md5=8b08d60fc30f4e00a590165488e0bc82
relation: 10.3390/s22176552
identifier: 10.3390/s22176552