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13 March 2015 Neuro-inspired smart image sensor: analog Hmax implementation
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Proceedings Volume 9403, Image Sensors and Imaging Systems 2015; 94030J (2015)
Event: SPIE/IS&T Electronic Imaging, 2015, San Francisco, California, United States
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.
© (2015) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Michel Paindavoine, Jérôme Dubois, and Purnawarman Musa "Neuro-inspired smart image sensor: analog Hmax implementation", Proc. SPIE 9403, Image Sensors and Imaging Systems 2015, 94030J (13 March 2015);


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