COMPHI1

The goal is to analyze overlapping objects in an image, usually at microscopic level and for industrial and medical purposes. The task consists of the following research topics: to detect objects which are possibly attached and/or overlapping and to segment the objects, i.e. estimate their contours. This project is a part of LUT Center of Excellence in Research, called Computational Photonics Imaging (COMPHI), in co-operation with LUT Applied Mathematics Laboratory, being associated with Academy of Finland's Center of Excellence in Research in Inverse Mathematics.

People

Sahar Zafari E-mail Office: 2419 Doctoral student
Tuomas Eerola E-mail Office: 2422 Tel: +358 40 139 3405 Post-Doctoral Researcher, Adjunct Professor
Jouni Sampo E-mail Office: 2508 Tel: +358 44 337 5672 University Lecturer
Heikki Kälviäinen E-mail Office: 2415 Tel: +358 40 586 7552 Professor
Heikki Haario E-mail Office: 2409 Tel: +358 400 814 092 Professor

Publications

Segmentation of Overlapping Convex Objects

By Sahar Zafari, Master's Thesis, Lappeenranta University of Technology, 2014.

The thesis presents a framework for segmentation of clustered overlapping convex objects.

Download: PDF

Segmentation of Overlapping Elliptical Objects in Silhouette Images

By Sahar Zafari, Tuomas Eerola, Jouni Sampo, Heikki Kälviäinen, and Heikki Haario, In IEEE Transactions on Image Processing 24 (12), 5942 - 5952, 2015.

This paper presents a radial symmetry based method for segmentation of clustered partially overlapping objects with a shape that can be approximated using an ellipse.

Download: PDF DOI code

Segmentation of Partially Overlapping Nanoparticles Using Concave Points

By Sahar Zafari, Tuomas Eerola, Jouni Sampo, Heikki Kälviäinen, and Heikki Haario, In International Symposium on Visual Computing (ISVC 2015), 2015.

This paper presens a method to segment multiple partially overlapping nanoparticles in images using concave points and ellipse properties.

Download: PDF DOI code

Segmentation of Partially Overlapping Convex Objects Using Branch and Bound Algorithm

By Sahar Zafari, Tuomas Eerola, Jouni Sampo, Heikki Kälviäinen, and Heikki Haario, In Asian Conference on Computer Vision (ACCV) workshop on mathematical and computational methods in biomedical imaging and image analysis (MCBMIIA2016), 2016.

This paper presents a method to segment multiple partially overlapping nanoparticles in images by formulating the task as a discrete optimization problem and by solving it using branch and bound algorithm.

Download: PDF DOI code

Comparison of Concave Point Detection Methods for Overlapping Convex Objects Segmentation

By Sahar Zafari, Tuomas Eerola, Jouni Sampo, Heikki Kälviäinen, and Heikki Haario, In the 20th Scandinavian Conference on Image Analysis (SCIA 2017), 2017.

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Resources

Software relases

  1. A radial symmetry based method for segmentation of overlapping objects
    Download the MATLAB code here.
    Please cite the following paper in any published work if you use this software.
    S. Zafari, T. Eerola, J. Sampo, H. Kalviainen, and H. Haario, Segmentation of Overlapping Elliptical Objects in Silhouette Images, IEEE Transactions on in Image Processing 24(12), 5942-5952, 2015.
  2. A method to segment overlapping nanoparticles using concave points
    Download the MATLAB code here.
    Please cite the following paper in any published work if you use this software.
    S. Zafari, T. Eerola, J. Sampo, H. Kalviainen, and H. Haario, Segmentation of Partially Overlapping Nanoparticles Using Concave Points, in International Symposium on Visual Computing (ISVC 2015), 2015.
  3. A method to segment overlapping nanoparticles using branch and bound algorithm
    Download the MATLAB code here.
    Please cite the following paper in any published work if you use this software.
    S. Zafari, T. Eerola, J. Sampo, H. Kalviainen, and H. Haario, Segmentation of Partially Overlapping Convex Objects Using Branch and Bound Algorithm, in Workshop on Mathematical and Computational Methods in Biomedical Imaging and Image Analysis (MCBMIIA2016), 2016.

Links