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Real Time Neuromorphic Camera Architecture Implemented with Quadratic Emphasis in an FPGA

Elizabeth Fonseca Chavez1, Mario A. Ibarra-Carrillo1, Julio C. Sosa2, and Ruben Ortega-Gonzalez1
1. Polytechnic/Escom, City of México, México
2. UNAM/Telecomm City of Mexico, Mexico
Abstract—A neuromorphic camera has one neuromorphic vision sensor which was designed to detect an approaching object in real time. This sensor is the “Dynamic Vision Sensor” (DVS) which works like a retina, but on a silicon chip. The DVS responds to changes in intensity under a wide range of lighting conditions and offers the possibility of fast, computationally efficient visual processing for navigation in mobile robotics. Reichardt proposed a model of fly´s vision such as the correlation-based “Elementary Motion Detector” (EMD). As a proposal, we present a new architecture for the EMD such that increases sensitivity. We call this new design the "EMD with emphasis". Because the "EMD with emphasis" requires more arithmetic operations than the classic EMD, it is implemented in a pipeline for its operation at a frequency of 25 MHz on a FPGA. The experimental results show that the performance of the proposed model is better than that of the classic model. The tests were successful for motion detection for size, contrast, as well as for movement: horizontal, expansion and rotation. Our system works with 30 fps and, a very low latency, dynamic range of 56dB, a resolution of 640x480. There are two special features: the first implies that the system operates with inexpensive cameras. The second characteristic has to do with the way the VHDL is used, ie, the system is easily transportable between FPGA branches.
 
Index Terms—neuromorphic, Reichardt, elementary motion detector, EMD, DVS, FPGA

Cite: Elizabeth Fonseca Chavez, Mario A. Ibarra-Carrillo, Julio C. Sosa, and Ruben Ortega-Gonzalez, "Real Time Neuromorphic Camera Architecture Implemented with Quadratic Emphasis in an FPGA," International Journal of Electronics and Electrical Engineering, Vol. 5, No. 3, pp. 230-234, June 2017. doi: 10.18178/ijeee.5.3.230-234
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