Realization of Processing Blocks of CNN Based CASA system on CPU and FPGA

SAVKAY O. L., Cesur E., Yildiz N., Yalcin M. E., Tavsanoglu V.

IEEE International Symposium on Circuits and Systems (ISCAS), Melbourne, Avustralya, 1 - 05 Haziran 2014, ss.2081-2084 identifier identifier

  • Yayın Türü: Bildiri / Tam Metin Bildiri
  • Doi Numarası: 10.1109/iscas.2014.6865576
  • Basıldığı Şehir: Melbourne
  • Basıldığı Ülke: Avustralya
  • Sayfa Sayıları: ss.2081-2084
  • İstanbul Teknik Üniversitesi Adresli: Evet

Özet

In this paper, hardware optimization of the preprocessing and software implementation of the processing blocks of a computer aided semen analysis (CASA) system are proposed, which is also implemented on an FPGA and ARM device as a working prototype. The software implementation of the track initialization, track maintenance, data validation and classification blocks of the processing part are implemented on a Zynq7000 ARM Cortex-A9 processor. In the preprocessing part, 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. The CASA system introduced in this paper is capable of processing full-HD 1080p@60 (1080 x 1920) video images in real-time.