On an Improved FPGA Implementation of CNN-Based Gabor-Type Filters

Abstract

In this brief, the details of the architecture of a previously introduced improved field-programmable gate array implementation of the cellular neural network (CNN)-based 2-D Gabor-type filter are given, and the implementation results are discussed. The proposed architecture is suitable for real-time applications with high pixel rates. The prototype is capable of processing video streams up to a pixel rate of 373.2 megapixels per second (MP/s), including full-high-definition (HD) 1080p@60 (1080 x 1920 resolution, 60-Hz frame rate, and 124.4-MP/s visible pixel rate). This brief also contains convergence rate analysis results, along with some discussions on FIR and CNN-based implementation methods.