Biologically-Inspired Digital Architecture for a Cortical Model of Orientation Selectivity
This paper presents a biologically inspired modular hardware implementation of a cortical model of orientation selectivity of the visual stimuli in the primary visual cortex targeted to a Field Programmable Gate Array (FPGA) device. The architecture mimics the functionality and organization of neurons through spatial Gabor-like filtering and the so-called cortical hypercolumnar organization. A systolic array and a suitable image addressing scheme are used to partially overcome the von Neumann bottleneck of monolithic memory organization in conventional microprocessor-based system by processing small and local amounts of sensory information (image tiles) in an incremental way. A real-time FPGA implementation is presented for 8 different orientations and aspects such as flexibility, scalability, performance and precision are discussed to show the plausibility of implementing biologically-inspired processing for early visual perception in digital devices.
KeywordsInput Image Clock Cycle Primary Visual Cortex Systolic Array Orientation Selectivity
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