The Journal of Korea Institute of Information, Electronics, and Communication Technology (한국정보전자통신기술학회논문지)

Korea Information Electronic Communication Technology (한국정보전자통신기술학회)
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Gradient Magnitude Hardware Architecture based on Hardware Folding Design Method for Low Power Image Feature Extraction Hardware Design

저전력 영상 특징 추출 하드웨어 설계를 위한 하드웨어 폴딩 기법 기반 그라디언트 매그니튜드 연산기 구조

  • Kim, WooSuk (Electrical, Electronic, and Control Engineering, HanKyong University) ;
  • Lee, Juseong (Center of Human-centered Interaction for Coexistence) ;
  • An, Ho-Myoung (Department of Electronics, Osan University)
  • Received : 2017.03.09
  • Accepted : 2017.03.30
  • Published : 2017.04.30
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Abstract

In this paper, a gradient magnitude hardware architecture based on hardware folding design method is proposed for low power image feature extraction. For the hardware complexity reduction, the projection vector chracteristic of gradient magnitude is applied. The proposed hardware architecture can be implemented with the small degradation of the gradient magnitude data quality. The FPGA implementation result shows the 41% of logic elements and 62% embedded multiplier savings compared with previous work using Altera Cyclone VI (EP4CE115F29C7N) FPGA and Quartus II v16.0 environment.

본 논문에서는 저전력 영상 특징 추출 하드웨어 설계를 위한 하드웨어 폴딩 기법 기반 저면적 Gradient magnitude 연산기 구조를 제안한다. 하드웨어 복잡도를 줄이기 위해 Gradient magnitude 벡터의 특징을 분석하여 기존 알고리즘을 하드웨어를 공유하여 사용할 수 있는 알고리즘으로 변경하여 Folding 구조가 적용될 수 있도록 했다. 제안된 하드웨어 구조는 기존 알고리즘의 특징을 최대한 이용했기 때문에 데이터 품질의 열화가 거의 없이 구현될 수 있다. 제안된 하드웨어 구조는 Altera Quartus II v16.0 환경에서 Altera Cyclone VI (EP4CE115F29C7N) FPGA를 이용하여 구현되었다. 구현 결과, 기존 하드웨어 구조를 이용하여 구현한 연산기와의 비교에서 41%의 logic elements, 62%의 embedded multiplier 절감 효과가 있음을 확인했다.

Keywords

References

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