Abstract: Cell migration, formation of cellular protrusions (e.g. blebs, filopodia), and structural reorganization are important phenomena in cell biology. Precise quantifications of movement/deformation are crucial to understand these processe at different levels of organization. We apply computer vision methods for combined optical flow (OF) and muti‐scale (MS) motion estimation of membrane translations, end growing and protrusion formation in fluorescence microscopy images. For these cases we bound OF error and optimal sampling rate, in order to guide biologists on their experimental conditions. We also show the advantages of OF methods compared with manual segmentation and tracking.

Active contour

I have made an example, with Matlab code included, related to both geometric- and geodesic level sets models. The example shows how the boundary separating inner- and outer parts of the segment can be driven temporally towards the image boundaries.

Jarno's Doctoral Thesis

Here it is, finally! Interested in segmenting disparity maps, or perhaps about robust image representation spaces for disparity calculation, or about variational disparity or optical-flow calculation? All this information, including one complete chapter explaining how the related models can be solved effiiently, can be found in the complete version of my phd thesis!

Prof. Steffen Härtel


Specialists Create a System that Analyses Male Infertility via Internet


Infertility affects roughly 15% of couples in Chile. It is estimated that annually around 6000 enquiries, related to infertility, are made to medical experts. However, not all the couples have the possibility of consulting an expert. Chile stretches over 4630km, is only 430km at the widest and has a population of 17 million. Therefore, the geography itself presents difficulties. In order to solve the problem, scientists at Instituto de Neurociencia Biomédica (Institute of Biomedical Neurosciences) have developed a centre of digital semen analysis based on Internet.

Nonlinear image diffusion


Recently I wrote a tutorial related to PDE based, nonlinear image diffusion, using AOS (Additive Operator Splitting) scheme to solve the related PDE (Partial Differential Equation) efficiently. It seems that that the 'matrix formulation' was not clear to everyone, so I have improved this part. I hope that now it is clearer and easier to understand. Also, I fixed a 'glitch' in the AOS-formulation.

Nonlinear image diffusion

A tutorial related to PDE based, nonlinear image diffusion, using AOS (Additive Operator Splitting) scheme to solve the related PDE (Partial Differential Equation) efficiently. The tutorial includes a PDF explaining all the steps needed to solve the PDE (showing how the solver is constructed, step-by-step) and a Matlab CODE. The tutorial also serves as a primer into the PDE based image treatment.



Paper "FROM SENSORS TO SPIKES: EVOLVING RECEPTIVE FIELDS TO ENHANCE SENSORIMOTOR INFORMATION IN A ROBOT-ARM", by Dr. (soon to be) Niceto Luque Sola and Dr. Jesús Garrido, has been accepted for publication in the International Journal of Neural Systems. My collaboration in this paper was related to parallelizing the EA (Evolutionary Algorithm) on the BioATC cluster at the University of Granada. Link to the article



A personal website of Dr. Jarno Ralli, with the idea of bringing 'science' closer to the end users, is under construction.The idea of this site is to communicate some of the latest findngs, both mine and my colleagues, related to machine vision, to anyone interested in the area. The idea is to include images, videos, program code, pdfs, and so on, in order for others to test with the techniques that we have developed. If you are interested in my, or my colleagues, work, please let me know!


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