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Proceedings Paper

Neuro-inspired smart image sensor: analog Hmax implementation
Author(s): Michel Paindavoine; Jérôme Dubois; Purnawarman Musa
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Paper Abstract

Neuro-Inspired Vision approach, based on models from biology, allows to reduce the computational complexity. One of these models - The Hmax model - shows that the recognition of an object in the visual cortex mobilizes V1, V2 and V4 areas. From the computational point of view, V1 corresponds to the area of the directional filters (for example Sobel filters, Gabor filters or wavelet filters). This information is then processed in the area V2 in order to obtain local maxima. This new information is then sent to an artificial neural network. This neural processing module corresponds to area V4 of the visual cortex and is intended to categorize objects present in the scene. In order to realize autonomous vision systems (consumption of a few milliwatts) with such treatments inside, we studied and realized in 0.35μm CMOS technology prototypes of two image sensors in order to achieve the V1 and V2 processing of Hmax model.

Paper Details

Date Published: 13 March 2015
PDF: 8 pages
Proc. SPIE 9403, Image Sensors and Imaging Systems 2015, 94030J (13 March 2015); doi: 10.1117/12.2079093
Show Author Affiliations
Michel Paindavoine, LEAD, CNRS, Univ. de Bourgogne (France)
Jérôme Dubois, Univ. de Picardie Jules Verne, INSSET (France)
Purnawarman Musa, Univ. of Gunadarma (Indonesia)


Published in SPIE Proceedings Vol. 9403:
Image Sensors and Imaging Systems 2015
Ralf Widenhorn; Antoine Dupret, Editor(s)

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