Abstract
The objective of this work is to simulate visual cortical cells, their sensitivities to frequencies and orientations, and their part in texture segmentation. The simulation of these cells is realised through band-pass, oriented filters (Gabor filters), and multiresolution image decomposition. By this means, the filter sensitivities represent cell sensitivities to preferred orientations according to their frequency and orientation bandwidths, and multiresolution represents the different band frequencies. For texture analysis and segmentation, overlaying of band-pass filters is necessary to completely cover the Fourier domain. A continuous sensitivity to frequency and orientation is achieved by the filters overlapping and consequently by their interpolation. We used here four octave frequency bands from 1 to 16 cycles deg−1 and six orientations per band. The results obtained for texture segmentation with these parameters are very promising (up to 97% recognition rate) [Guérin-Dugué and Palagi, 1994 Neural Processing Letters1(1) 25 – 29]. The images analysed cover a multitude of different domains such as psychophysical tests and natural textures of different roughness. In order to create a cortical cell representation closer to neurophysiological data, and to improve texture segmentation results, we represent cell sensitivities by their foveal and parafoveal projections [R L DeValois, K K DeValois, 1988 Spatial Vision (Oxford: Oxford Science Publications)]. Cells receiving projections from the foveal zone are modeled by five octave frequency bands (from 0.5 to 16 cycles deg−1) and six orientations. Cells receiving projections from the parafoveal zone have the same sensitivities but are modeled by four octave frequency bands (from 0.5 to 8 cycles deg−1). By using these two different resolutions, preliminary tests have shown the capability of detecting textured regions by the parafoveal projection and localisation of boundaries by the foveal projection.
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