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Open Access

C-HMAX: Artificial Cognitive Model Inspired by the Color Vision Mechanism of the Human Brain

State Key Laboratory of Intelligent Technology and Systems, Tsinghua National Laboratory for Information Science and Technology, Department of Computer Science and Technology, Tsinghua University, Beijing 100084, China
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Abstract

Artificial cognitive models and computational neuroscience methods have garnered great interest from both neurologist and leading analysts in recent years. Among the cognitive models, HMAX has been widely used in computer vision systems for its robustness shape and texture features inspired by the ventral stream of the human brain. This work presents a Color-HMAX (C-HMAX) model based on the HMAX model which imitates the color vision mechanism of the human brain that the HMAX model does not include. C-HMAX is then applied to the German Traffic Sign Recognition Benchmark (GTSRB) which has 43 categories and 51 840 sample traffic signs with an accuracy of 98.41%, higher than most other models including linear discriminant analysis and multi-scale convolutional neural network.

Keywords

machine learningartificial cognitive modeltraffic sign recognition

References

[1]
D. J. Ingle, M. A. Goodale, and R. J. W. Mansfield, Analysis of Visual Behavior. Boston, America: MIT Press, 1982.
[2]
M. A. Goodale and A. D. Milner, Separate visual pathways for perception and action, Trends in Neuroscience, vol. 15, no. 1, pp.20-25, Jan. 1992.
Crossref Google Scholar
[3]
J. Jin, Y. Wang, H. A. Swadlow, and J. M. Alonso, Population receptive fields of ON and OFF thalamic inputs to an orientation column in visual cortex, Nat. Neurosci., vol. 14, no. 2, pp.232-238, Jan. 2011.
Crossref Google Scholar
[4]
M. S. Gazzaniga, R. B. Ivry, and G. R. Mangun, Cognitive Neuroscience, 2nd Ed. New York, America: W W Norton & Co Inc (Np), 2002.
[5]
T. J. Bussey and L. M. Saksida, Memory, perception, and the ventral visual-perirhinal-hippocampal stream: Thinking outside of the boxes, Hippocampus, vol. 17, no. 9, pp.898-908, Sep. 2007.
Crossref Google Scholar
[6]
T. M. Preuss, I. Stepniewska, and J. H. Kaas, Movement representation in the dorsal and ventral premotor areas of owl monkeys: A microstimulation study, J. Comp. Neurol., vol. 371, no. 4, pp.649-676, Aug. 1996.
Crossref
[7]
R. Gattas, A. P. Sousa, M. Mishkin, and L. G. Ungerleider, Cortical projections of area V2 in the Macaque, Cereb. Cortex., vol. 7, no. 2, pp.110-129, Jul. 1997.
Crossref Google Scholar
[8]
D. Y. Ts’o, M. Zarella, and G. Burkitt, Whither the hypercolumn, Journal of Physiology, vol. 587, no. 12, pp.2791-2805, Jun. 2009.
Crossref Google Scholar
[9]
M. Riesenhuber and T. Poggio, Hierarchical models of object recognition in cortex, Nature Neuroscience, vol. 2, no. 11, pp.1019-1025, Feb. 1999.
Crossref Google Scholar
[10]
T. Serre and T. Poggio, Reverse-engineering the brain, Communications of the Association for Computing Machinery, vol. 53, no. 10, pp.54-61, Oct. 2010.
Crossref Google Scholar
[11]
T. Serre, L. Wolf, and T. Poggio, Object recognition with features inspired by visual cortex, presented at the 2005 IEEE Conference on Computer Vision and Pattern Recognition, San Diego, USA, 2005.
Crossref
[12]
J. Mutch and D. G. Lowe, Multiclass object recognition with sparse, localized features, presented at the 2006 IEEE Conference on Computer Vision and Pattern Recognition, New York, USA, 2006.
[13]
N. W. Daw, Goldfish Retina: Organization for simultaneous color contrast, Science, vol. 158, no. 3803, pp. 942-944, Nov. 1967.
Crossref Google Scholar
[14]
B. R. Conway, Neural Mechanisms of Color Vision: Double-Opponent Cells in the Visual Cortex. Dordrecht, Netherlands: Kluwer Academic Press, 2002.
Crossref
[15]
J. E. Dowling, Neurons and Networks: An Introduction to Behavioral Neuroscience, 2nd Ed. Massachusetts, USA: Belknap Press of Harvard University Press, 2001.
[16]
J. Stallkamp, M. Schlipsing, J. Salmen, and C. Igel, Man vs. computer: Benchmarking machine learning algorithms for traffic sign recognition, Neural Networks, vol. 32, no. 1, pp. 323-332, Aug. 2012.
Crossref Google Scholar
Tsinghua Science and Technology
Volume 18 Issue 1,
February 2013
Pages 51-56
DOI: 10.1109/TST.2013.6449407
Cite this article:
Yang B, Zhou L, Deng Z. C-HMAX: Artificial Cognitive Model Inspired by the Color Vision Mechanism of the Human Brain. Tsinghua Science and Technology, 2013, 18(1): 51-56. https://doi.org/10.1109/TST.2013.6449407

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Received: 15 October 2012
Accepted: 19 December 2012
Published: 07 February 2013
© The author(s) 2013
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