Realization of preprocessing blocks of CNN based CASA system on FPGA

O. Levent Savkay, Nerhun Yildiz, Evren Cesur, Mustak E. Yalcin, Vedat Tavsanoglu

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

6 Citations (Scopus)

Abstract

In this paper, hardware optimization of the preprocessing part of a computer aided semen analysis (CASA) system is proposed, which is also implemented on an FPGA device as a working prototype. A real-time cellular neural network (CNN) emulator (RTCNNP-v2) is used for the realization of the image processing algorithms, whose regular, flexible and reconfigurable infrastructure simplifies the prototyping process. For future work, the post-processing part of the CASA system is proposed to be implemented on the same FPGA device as software, using either a soft or hard processor core. By the integration of the pre- and post-processing parts, the designed CASA system will be capable of processing full-HD 1080p@60 (1080×1920) video images in real-time.

Original languageEnglish
Title of host publication2013 European Conference on Circuit Theory and Design, ECCTD 2013 - Proceedings
PublisherIEEE Computer Society
ISBN (Print)9783000437854
DOIs
Publication statusPublished - 2013
Event2013 European Conference on Circuit Theory and Design, ECCTD 2013 - Dresden, Germany
Duration: 8 Sept 201312 Sept 2013

Publication series

Name2013 European Conference on Circuit Theory and Design, ECCTD 2013 - Proceedings

Conference

Conference2013 European Conference on Circuit Theory and Design, ECCTD 2013
Country/TerritoryGermany
CityDresden
Period8/09/1312/09/13

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