M
Mongi A. Abidi
Researcher at University of Tennessee
Publications - 366
Citations - 7941
Mongi A. Abidi is an academic researcher from University of Tennessee. The author has contributed to research in topics: Image processing & Image segmentation. The author has an hindex of 42, co-authored 365 publications receiving 7573 citations. Previous affiliations of Mongi A. Abidi include Centre national de la recherche scientifique & Oak Ridge National Laboratory.
Papers
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Journal ArticleDOI
Recent advances in visual and infrared face recognition: a review
TL;DR: This paper provides an up-to-date review of research efforts in face recognition techniques based on two-dimensional images in the visual and infrared (IR) spectra.
Book
Data fusion in robotics and machine intelligence
TL;DR: This chapter discusses data fusion and sensor integration - state-of-the-art 1990s, R.C. Kak data fusion techniques using robust statistics and Y. Mintz recursive fusion operators - desirable properties and illustrations.
Journal ArticleDOI
Gray-level grouping (GLG): an automatic method for optimized image contrast Enhancement-part I: the basic method
TL;DR: The basic procedure is to first group the histogram components of a low-contrast image into a proper number of bins according to a selected criterion, then redistribute these bins uniformly over the grayscale, and finally ungroup the previously grouped gray-levels.
Journal ArticleDOI
Multiscale Fusion of Visible and Thermal IR Images for Illumination-Invariant Face Recognition
Seong G. Kong,Jingu Heo,Faysal Boughorbel,Yue Zheng,Besma Abidi,Andreas Koschan,Mingzhong Yi,Mongi A. Abidi +7 more
TL;DR: In this paper, an ellipse fitting method was used to detect eyeglass regions and replaced with eye template patterns to preserve the details useful for face recognition in the fused image.
Journal ArticleDOI
Detection and classification of edges in color images
Andreas Koschan,Mongi A. Abidi +1 more
TL;DR: Various vector-valued techniques for detecting discontinuities in color images are discussed, mainly based on vector order statistics, followed by presentation by examples of a couple of results of color edge detection.