Demo: An improved FPGA implementation of CNN Gabor-type Filters

In this paper, a new Cellular Neural Network (CNN) structure for implementing two dimensional Gabor-type filters is proposed over our previous design. The structure is coded in VHDL and realized on a state of the art Altera Stratix IV 230 FPGA. The prototype supports Full-HD 1080p resolution and 60...

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Bibliographic Details
Published in2012 13th International Workshop on Cellular Nanoscale Networks and their Applications pp. 1 - 2
Main Authors Cesur, E., Yildiz, N., Tavsanoglu, V.
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.08.2012
Subjects
Cellular neural networks
Educational institutions
Electronic mail
Field programmable gate arrays
Gabor filters
Real-time systems
Streaming media
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Summary:In this paper, a new Cellular Neural Network (CNN) structure for implementing two dimensional Gabor-type filters is proposed over our previous design. The structure is coded in VHDL and realized on a state of the art Altera Stratix IV 230 FPGA. The prototype supports Full-HD 1080p resolution and 60 Hz frame rate. One dedicated processor is used for each Euler iteration, where time step is taken as the same as optimum step size, and 50 iterations are implemented. The input/output, control, RAM and communication blocks of the realization are taken from our second generation real time CNN emulator (RTCNNP-v2).
ISBN:9781467302876
1467302872
ISSN:2165-0144
2165-0152
DOI:10.1109/CNNA.2012.6331472