Saturday, May 3, 2014

Simple Trial for Border Ownership Detection

I implemented a simple algorithm to determine the border ownership in a visual receptive field.  The idea is based on the physiological finding that there are neurons in the visual field, excitatory for cross-directional nearby edges and inhibitory for iso-directional nearby edges.  Researchers such as Sakai and Nishimura (2006) have proposed models of border ownership coding with this finding.
What I have done is:
  • Apply Gabor filters to find 0° and 90° edges.
  • Sum up excitatory and inhibitory effects for cross and iso-directional nearby edges.
  • Determine which side is more excitatory for each edge.
(Coding was done with OpenCV Java API.)

The following are sample pictures:
Fig1: the input
Fig2: Gabor filter applied (0°)
(There are two edge lines for
the right side due to, perhaps,
the phase setting of Gabor filter.)
Fig3: Gabor filter applied (90°)
Fig4: Border ownership detected
(indicated with gray area in either
side of edges (Fig2 + Fig))


The experiment was part of my attempt to find an algorithm for identifying Spelke's objects.  While the algorithm I tried above may be a heuristics used in the brain, it does not seem so straightforward to represent the coherence of Spelke's objects such as local color coherence over time.  So, I leave the result above as tentative and go for exploring other algorithms.  Besides, to make the algorithm efficient, I would have to hack around the code (it took 15 seconds to process the Lenna picture without sensible result).