Abstract
This paper presents a biologically inspired modular hardware implementation of a cortical model of orientation selectivity of the visual stimuli in the primary visual cortex targeted to a Field Programmable Gate Array (FPGA) device. The architecture mimics the functionality and organization of neurons through spatial Gabor-like filtering and the so-called cortical hypercolumnar organization. A systolic array and a suitable image addressing scheme are used to partially overcome the von Neumann bottleneck of monolithic memory organization in conventional microprocessor-based system by processing small and local amounts of sensory information (image tiles) in an incremental way. A real-time FPGA implementation is presented for 8 different orientations and aspects such as flexibility, scalability, performance and precision are discussed to show the plausibility of implementing biologically-inspired processing for early visual perception in digital devices.
Keywords
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
Ferster, D., Miller, K.D.: Neural mechanisms of orientation selectivity in the visual cortex. Annu. Rev. Neurosci. 23, 441–471 (2000)
Rust, N.C., Shwartz, O., Movshon, J.A., Simoncelli, E.: Spatiotemporal elements of macaque v1 receptive field. Neuron 46, 945–956 (2005)
Itti, L., Koch, C.: Computational modeling of visual attention. Nature Reviews NeuroscienceNature Reviews Neuroscience 2(3), 194–203 (2003)
Mead, C.A.: Neuromorphic electronic systems. Proc. IEEE 78, 1629–1636 (1990)
Choi, T.Y.W., Shi, B.E., Bohanen, K.A.: A multi-chip implementation of cortical orientation hypercolumns. In: Proceedings ISCAS, pp. 13–16 (2004)
Choi, T.Y.W., Merolla, P.A., Arthur, J.V., Bohanen, K.A., Shi, B.E.: Neuromorphic implementation of orientation hypercolumn. IEEE Transactions on Circuits and Systems -I 52(6), 1049–1060 (2005)
Herbordt, M.C., VanCourt, T., Gu, Y., Sukhwani, B., Conti, A., Model, J., DiSabello, D.: Achieving high performance with fpga-based computing. IEEE Computer Magazine, 50–57 (March 2007)
Girau, B., Torres-Huitzil, C.: Massively distributed digital implementation of an integrate-and.fire legion network for visual scene segmentation. Neurocomputing 50, 1186–1197 (2007)
Torres-Huitzil, C., Girau, B., Gauffriau, A.: Hardware/software co-design for embedded implementation of neural networks. In: Diniz, P.C., Marques, E., Bertels, K., Fernandes, M.M., Cardoso, J.M.P. (eds.) ARCS 2007. LNCS, vol. 4419, pp. 167–178. Springer, Heidelberg (2007)
Tsi, D.M., Lin, C.P., Huang, K.T.: Defect detection in coloured texture surfaces using gabor filters. The Imaging Science Journal 53, 27–37 (2005)
Petkov, N., Kruzinga, P.: Computational models of visual neurons specialised in the detection of periodic and aperiodic oriented visual stimuli: Bar and gratings cells. Biological Cybernetics 75, 83–96 (1997)
Grigorescu, S.E., Petkov, N., Kruizinga, P.: Comparison of texture features based on gabor filter. IEEE Transactions on Neural Networks 11(10), 1160–1167 (2002)
Torres-Huitzil, C., Arias-Estrada, M.: Fpga-based configurable hardware architecture for real-time window-based image processing. EURASIP Journal on Applied Signal Processing 7, 1024–1034 (2005)
Himavathi, S., Anitha, D., Muthuramalingam, A.: Feedforward neural network implementation in fpga using layer multiplexing for effective resource utilization. IEEE Transactions on Neural Networks 18(3), 880–888 (2007)
Kung, H.T.: Why systolic architectures? IEEE Computer 15(1), 37–46 (1982)
Savich, A.W., Moussa, M., Areibi, S.: The impact of arithmetic representation on implementing mlp-bp on fpgas: A study. IEEE Transactions on Neural Networks 18(1), 240–252 (2007)
Adelson, E.H., Berge, J.R.: Spatiotemporal energy models for the perception of motion. J. Opt. Soc. Am. A 2(2) (February 1985)
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 2008 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Torres-Huitzil, C., Girau, B., Arias-Estrada, M. (2008). Biologically-Inspired Digital Architecture for a Cortical Model of Orientation Selectivity. In: Kůrková, V., Neruda, R., Koutník, J. (eds) Artificial Neural Networks - ICANN 2008. ICANN 2008. Lecture Notes in Computer Science, vol 5164. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-87559-8_20
Download citation
DOI: https://doi.org/10.1007/978-3-540-87559-8_20
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-87558-1
Online ISBN: 978-3-540-87559-8
eBook Packages: Computer ScienceComputer Science (R0)