A fully pipelined and parallel hardware architecture for real-time BRISK salient point extraction

  • Ehsan Azimi
  • Alireza Behrad
  • Mohammad Bagher Ghaznavi-Ghoushchi
  • Jamshid Shanbehzadeh
Original Research Paper


Scale and rotation invariant salient point detection and matching algorithms are variously used in computer vision applications such as image matching, 3D localization and pose estimation. Recently, hardware implementation of image and video processing algorithms has emerged as a viable solution to handle the high computational complexity of applications like 3D pose estimation with several processing stages. The hardware implementation of various stages of theses algorithms can be executed in a pipelined manner to ensure the reality of time. In this paper, a new and fully pipelined hardware architecture is proposed for salient point detection using Binary Robust Invariant Scalable Keypoints (BRISK) algorithm. BRISK algorithm is a binary keypoint extractor that detects salient points by constructing a scale-space pyramid; therefore, its fixed-point hardware implementation in a pipelined manner is challenging because of the required synchronization for various layers in scale domain. The proposed hardware architecture was implemented using Verilog Hardware Description Language, and the functionality of the design was validated through several experiments. The proposed design was synthesized by using an ASIC digital design flow utilizing 180 nm CMOS technology as well as a Virtex-4 FPGA. The design is clocked at 90.91 MHz in ASIC implementation and achieves processing rate of 169.29 frames/s while running on input images with 800 × 600 resolution. The throughput of FPGA implementation is 180.44 frames/s with 96.89 MHz clock frequency for the same input image resolution. Experimental results confirm the efficiency of the proposed hardware architecture in comparison with software implementation.


BRISK salient points Feature extraction Application-specific integrated circuit (ASIC) Hardware implementation 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2017

Authors and Affiliations

  • Ehsan Azimi
    • 1
  • Alireza Behrad
    • 2
  • Mohammad Bagher Ghaznavi-Ghoushchi
    • 2
  • Jamshid Shanbehzadeh
    • 3
  1. 1.Department of Computer Engineering, Science and Research BranchIslamic Azad UniversityTehranIran
  2. 2.Electrical Engineering DepartmentShahed UniversityTehranIran
  3. 3.Department of Computer EngineeringKharazmi UniversityTehranIran

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