Suppression of contour perception by band-limited noise and its relation to nonclassical receptive field inhibition

Petkov, Nicolai; Westenberg, Michel A.

doi:10.1007/s00422-002-0378-2

Cited by 94 publications

(92 citation statements)

References 19 publications

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“…We now specify the choice of parameter values that is used in the current work. The parameterization that we use to model the spatial properties follows previous works (Petkov and Kruizinga 1997;Kruizinga and Petkov 1999;Petkov and Westenberg 2003;Grigorescu et al 2003) and takes into account some restrictions found in experimental data. The spatial aspect ratio is set to γ = 0.5 for which the support of the receptive field is elongated along theȳ axis.…”

Section: Appendix A: Mathematical Details Of the Crf Functionmentioning

confidence: 99%

Motion detection, noise reduction, texture suppression, and contour enhancement by spatiotemporal Gabor filters with surround inhibition

Petkov

Subramanian

2007

Biol Cybern

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We study the orientation and speed tuning properties of spatiotemporal three-dimensional (3D) Gabor and motion energy filters as models of time-dependent receptive fields of simple and complex cells in the primary visual cortex (V1). We augment the motion energy operator with surround suppression to model the inhibitory effect of stimuli outside the classical receptive field. We show that spatiotemporal integration and surround suppression lead to substantial noise reduction. We propose an effective and straightforward motion detection computation that uses the population code of a set of motion energy filters tuned to different velocities. We also show that surround inhibition leads to suppression of texture and thus improves the visibility of object contours and facilitates figure/ground segregation and the detection and recognition of objects.

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Section: Appendix A: Mathematical Details Of the Crf Functionmentioning

confidence: 99%

Motion detection, noise reduction, texture suppression, and contour enhancement by spatiotemporal Gabor filters with surround inhibition

Petkov

Subramanian

2007

Biol Cybern

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“…For this reason, numerous neural network approaches have been proposed that are inspired by the physiology of the primary visual cortex (Ben-Shahar and Zucker, 2004;Grigorescu et al, 2003Grigorescu et al, , 2004Hansen and Neumann, 2008;Huang et al, 2009;Li, 1998;Mundhenk and Itti, 2005;Papari et al, 2007;Papari and Petkov, 2011;Petkov and Westenberg, 2003;Tang et al, 2007a,b;Ursino and La Cara, 2004;Vonikakis et al, 2006;Zeng et al, 2011a,b). A neuron in such a model has a classical receptive field (cRF), often defined using a Gabor function, that receives input from the image.…”

Section: Introductionmentioning

confidence: 99%

Image Segmentation Using a Sparse Coding Model of Cortical Area V1

Spratling

2013

IEEE Trans. on Image Process.

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Algorithms that encode images using a sparse set of basis functions have previously been shown to explain aspects of the physiology of primary visual cortex (V1), and have been used for applications such as image compression, restoration, and classification. Here, a sparse coding algorithm, that has previously been used to account of the response properties of orientation tuned cells in primary visual cortex, is applied to the task of perceptually salient boundary detection. The proposed algorithm is currently limited to using only intensity information at a single scale. However, it is shown to out-perform the current state-of-the-art image segmentation method (Pb) when this method is also restricted to using the same information.

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“…4b show the structures of the resulting two COSFIRE filters. For more technical details about the Gabor filters and the COSFIRE configuration method, we refer the reader to [3,[5][6][7][8][10][11][12] and to an online implementation 2 . We only mention that the configuration of a COSFIRE filter takes as input three parameters, a set of wavelengths λ and a set of orientations θ that characterize a bank of Gabor filters, together with a set of radius values ρ that represent a number of concentric circles around the center of the filter along which the Gabor filter responses are considered.…”

Section: Configuration Of a Cosfire Filter With Inhibitionmentioning

confidence: 99%

Recognition of Architectural and Electrical Symbols by COSFIRE Filters with Inhibition

Guo

Shi

Azzopardi

et al. 2015

Computer Analysis of Images and Patterns

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Abstract. The automatic recognition of symbols can be used to automatically convert scanned drawings into digital representations compatible with computer aided design software. We propose a novel approach to automatically recognize architectural and electrical symbols. The proposed method extends the existing trainable COSFIRE approach by adding an inhibition mechanism that is inspired by shape-selective TEO neurons in visual cortex. A COSFIRE filter with inhibition takes as input excitatory and inhibitory responses from line and edge detectors. The type (excitatory or inhibitory) and the spatial arrangement of low level features are determined in an automatic configuration step that analyzes two types of prototype pattern called positive and negative. Excitatory features are extracted from a positive pattern and inhibitory features are extracted from one or more negative patterns. In our experiments we use four subsets of images with different noise levels from the Graphics Recognition data set (GREC 2011) and demonstrate that the inhibition mechanism that we introduce improves the effectiveness of recognition substantially.

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Suppression of contour perception by band-limited noise and its relation to nonclassical receptive field inhibition

Cited by 94 publications

References 19 publications

Motion detection, noise reduction, texture suppression, and contour enhancement by spatiotemporal Gabor filters with surround inhibition

Motion detection, noise reduction, texture suppression, and contour enhancement by spatiotemporal Gabor filters with surround inhibition

Image Segmentation Using a Sparse Coding Model of Cortical Area V1

Recognition of Architectural and Electrical Symbols by COSFIRE Filters with Inhibition

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