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

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3 Author(s)
Evren Cesur ; Dept. of Electron. & Commun. Eng., Yildiz Tech. Univ., Istanbul, Turkey ; Nerhun Yildiz ; Vedat Tavsanoglu

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 × 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.

Published in:

IEEE Transactions on Circuits and Systems II: Express Briefs  (Volume:59 ,  Issue: 11 )