Authors:
Fernando Perez-Peña
1
;
Arturo Morgado-Estevez
1
;
Rafael J. Montero-Gonzalez
1
;
Alejandro Linares-Barranco
2
and
Gabriel Jimenez-Moreno
2
Affiliations:
1
University of Cadiz, Spain
;
2
University of Seville, Spain
Keyword(s):
Bio-inspired, Video, Industrial Surveillance, Spike, Retinomorphic Systems, Address Event Representation.
Related
Ontology
Subjects/Areas/Topics:
Multimedia
;
Multimedia Signal Processing
;
Neural Networks, Spiking Systems, Genetic Algorithms and Fuzzy Logic
;
Sensors and Multimedia
;
Telecommunications
Abstract:
Nowadays we live in very industrialization world that turns worried about surveillance and with lots of occupational hazards. The aim of this paper is to supply a surveillance video system to use at ultra fast industrial environments. We present an exhaustive timing analysis and comparative between two different Address Event Representation (AER) retinas, one with 64x64 pixel and the other one with 128x128 pixel in order to know the limits of them. Both are spike based image sensors that mimic the human retina and designed and manufactured by Delbruck’s lab. Two different scenarios are presented in order to achieve the maximum frequency of light changes for a pixel sensor and the maximum frequency of requested pixel addresses on the AER output. Results obtained are 100 Hz and 1.88 MHz at each case for the 64x64 retina and peaks of 1.3 KHz and 8.33 MHz for the 128x128 retina. We have tested the upper spin limit of an ultra fast industrial machine and found it to be approximately 6000
rpm for the first retina and no limit achieve at top rpm for the second retina. It has been tested that in cases with high light contrast no AER data is lost.
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