T
Thierry Pun
Researcher at University of Geneva
Publications - 358
Citations - 17941
Thierry Pun is an academic researcher from University of Geneva. The author has contributed to research in topics: Digital watermarking & Watermark. The author has an hindex of 49, co-authored 358 publications receiving 15919 citations. Previous affiliations of Thierry Pun include National Institutes of Health & École Polytechnique Fédérale de Lausanne.
Papers
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Journal ArticleDOI
Computer automated lanes detection and profiles evaluation of one-dimensional gel electrophoretic autoradiograms
TL;DR: A new fast, precise and reproducible method for lanes detection and profiles evaluation of one‐dimensional gel electrophoretic autoradiograms is presented, and its principles are based on image and signal processing techniques.
Proceedings ArticleDOI
Color-audio encoding interface for visual substitution: see color matlab-based demo
TL;DR: The experimental tests using a demo implementation have shown the feasibility and usefulness of the general framework for color-audio encoding of images to provide visually impaired individuals with a low-cost application for color perception substitution, using the sense of hearing instead of sight.
Multisource Sonification for Visual Substitution in an Auditory Memory Game: One, or Two Fingers?
TL;DR: The present work addresses the optimal use of auditory-multi-touch interaction, and in particular the matter of the number of fingers needed for efficient exploration, and shows that for an easy task aiming at matching few objects, the use of two fingers is moderately more efficient than theUse of one finger.
Book Chapter
Multimodal authentication based on random projections and distributed coding
TL;DR: This paper considers an authentication framework for independent modalities based on binary hypothesis testing using source coding jointly with the random projections and the impact of modality fusion on the authentication system performance is demonstrated.
Book ChapterDOI
Visual Indexing with an Attentive System
TL;DR: A new architecture for a general-purpose computer vision system whose design principles have been inspired by the study of human vision is proposed, respectively called “what” and “where” subsystems.