Adrian Ciobanu
Romanian Academy
42 Papers
112 Citations
Adrian Ciobanu is an academic researcher from Romanian Academy. The author has contributed to research in topics: Feature vector & Feature extraction. The author has an hindex of 7, co-authored 39 publications. Previous affiliations of Adrian Ciobanu include University of the Algarve.
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Papers
The Sellaphora pupula species complex (Bacillariophyceae): morphometric analysis, ultrastructure and mating data provide evidence for five new species
David G. Mann,Sarah M. McDonald,Micha Bayer,Stephen J. M. Droop,Victor A. Chepurnov,R.E. Loke,Adrian Ciobanu,J. M. Hans du Buf +7 more
TL;DR: A new morphometric method, contour segment analysis, which was recently developed for diatoms in relation to automated identification, gives a clear separation of all six genodemes and indicates no heterogeneity within each.
Diatom identification: a double challenge called ADIAC
H. Du Buf,Micha Bayer,Stephen J. M. Droop,R. Head,Steve Juggins,S. Fischer,Horst Bunke,Michael H. F. Wilkinson,Jos B. T. M. Roerdink,Jose Luis Pech-Pacheco,Gabriel Cristóbal,Hamid Reza Shahbazkia,Adrian Ciobanu +12 more
- 27 Sep 1999
TL;DR: The main goal is to develop algorithms for an automatic identification of diatoms using image information, both valve shape (contour) and ornamentation, as well as first results on shape modeling and contour extraction.
Multimodal biometric authentication based on voice, face and iris
Tudor Barbu,Adrian Ciobanu,Mihaela Luca +2 more
- 01 Nov 2015
TL;DR: A multimodal biometric system based on three identifiers: iris, voice and faces, which is approached by using SIFT-based features and LAB-based iris recognition approach is proposed.
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Image Categorization Based on Computationally Economic LAB Colour Features
Adrian Ciobanu,Mihaela Costin,Tudor Barbu +2 more
- 01 Jan 2013
TL;DR: An easy to compute and small colour feature vector is introduced in this paper, as a tool to be used in the process of retrieval or classification of similarly coloured digital images from very large databases.
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Iris classification using WinICC and LAB color features
Ioan Pavaloi,Adrian Ciobanu,Mihaela Luca +2 more
- 01 Nov 2013
TL;DR: The WinICC software package is presented, designed to help in tasks like clusterization or classification of images based on different feature vectors, and a result that may suggest a possible identification of human irises based on color distribution is suggested.
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