Nataliya Strokina
Postdoctoral researcher
Computer Vision Group
Department of Signal Processing
Faculty of Computing and Electrical Engineering
Tampere University of Technology, Finland
Korkeakoulunkatu 10, FI-33720 Tampere, FINLAND
PO Box 527, FI-33101 Tampere, FINLAND
Office: TF310 (Tietotalo)
E-mail: firstname.lastname@tut.fi
Research: Nataliya is working in the FishView project the goal of which is to develop a robot that can swim upstream and find its own hydrodynamically efficient way through the flow.

The topic of Nataliya's PhD work was Image Processing and Analysis Methods for Pulp Process Measurement that is carried out in the PulpVision Project. The goal of the project is to develop image analysis methods that would allow the paper- and pulpmaking industies to reach a resource efficient and environmentally sound production.
Current project:
N. Strokina, J. Kämäräinen, J. Tuhtan, J. Fuentes-Peres, M. Kruusmaa.
Joint estimation of bulk flow velocity and angle using a lateral line probe.
IEEE Tranascations on Instrumentation and Measurements, 2015. Accepted for publication.
N. Muhammad, N. Strokina, G. Toming, J. Tuhtan, J. Kämäräinen, M. Kruusmaa.
Flow feature extraction for underwater robot localization: preliminary results.
In the IEEE International Conference on Robotics and Automation, ICRA2015.
J. Tuhtan, N. Strokina, G. Toming, N. Muhammad, M. Kruusmaa, J. Kämäräinen.
Hydrodynamic classification of natural flows using an artificial lateral line and frequency features.
In the 36th Hydro-Environmaental Engineering and Research World Congress, IAHR2015.
N. Strokina, J. Kämäräinen, M. Kruusmaa, J. Tuhtan.
FishView: environment investigation methods for an underwater robot.
Federated Computer Science Event, Lappeenranta, Finland, 2014.
Publications from previous projects:
H. Mutikainen, N. Strokina, T. Eerola, L. Lensu, H. Kälviäinen, and J. Käyhkö
Online measurement of the bubble size distribution in medium-consistency oxygen delignification.
Accepted for publication in Appita Journal. 2015.
M. Sorokin, N. Strokina, T. Eerola, L. Lensu, and H. Kälviäinen,
Image-based characterization of the pulp flows.
In the 9th Open German-Russian Workshop on Pattern Recognition and Image Understanding (OGRW 2014), 2014.
N. Strokina, R. Juranek, T. Eerola, L. Lensu, P. Zemcik, H. Kälviäinen.
Comparison of Appearance-based and Geometry-based Bubble Detectors.
The International Conference on Computer Vision and Graphics ICCVG 2014, Warsaw, Poland, 2014.
N. Strokina.
Machine Vision Methods for Pulp Process Measurements.
Doctoral thesis. Lappeenranta University of Technology. November 15, 2013.
N. Strokina, A. Mankki, T. Eerola, L. Lensu, J. Käyhkö, H. Kälviäinen.
Framework for developing image-based dirt particle classifiers for dry pulp sheets.
Machine Vision and Applications Journal, 24(4): pp 869-881, 2013.
N. Strokina, T. Kurakina, T. Eerola, L. Lensu, H. Kälviäinen.
Detection of Curvilinear Structures by Tensor Voting Applied to Fiber Characterization.
Scandinavian Conference on Image Analysis SCIA 2013.
Lecture Notes in Computer Science, 7944: pp 22-33, 2013.
N. Strokina, J. Matas, T. Eerola, L. Lensu, H. Kälviäinen.
Detection of Bubbles as Concentric Circular Arrangements.
In the Proceedings of the 21st International Conference on Pattern Recognition ICPR 2012, pp 2655 - 2659.
N. Strokina, A. Mankki, T. Eerola, L. Lensu, J. Käyhkö, H. Kälviäinen.
Semisynthetic ground truth for dirt particle counting and classification methods.
IAPR Conference on Machine Vision Applications MVA 2011.
N. Strokina, T. Eerola, L. Lensu, H. Kälviäinen.
Adaptive classification of dirt particles in papermaking process.
Scandinavian Conference on Image Analysis SCIA 2011.
L. Laaksonen, N. Strokina, T. Eerola, L. Lensu, H. Kälviäinen.
Improving particle segmentation from process images with Wiener filtering.
Scandinavian Conference on Image Analysis SCIA 2011.
N. Strokina.
Learning Robot Motions from Visual Sensing.
Master's thesis. Lappeenranta University of Technology. May30, 2010.