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基于FPGA的水平集图像分割算法加速器

刘野 肖剑彪 吴飞 常亮 周军

刘野, 肖剑彪, 吴飞, 常亮, 周军. 基于FPGA的水平集图像分割算法加速器[J]. 电子与信息学报, 2021, 43(6): 1525-1532. doi: 10.11999/JEIT210012
引用本文: 刘野, 肖剑彪, 吴飞, 常亮, 周军. 基于FPGA的水平集图像分割算法加速器[J]. 电子与信息学报, 2021, 43(6): 1525-1532. doi: 10.11999/JEIT210012
Ye LIU, Jianbiao XIAO, Fei WU, Liang CHANG, Jun ZHOU. A Fast and Efficient FPGA-based Level Set Hardware Accelerator for Image Segmentation[J]. Journal of Electronics & Information Technology, 2021, 43(6): 1525-1532. doi: 10.11999/JEIT210012
Citation: Ye LIU, Jianbiao XIAO, Fei WU, Liang CHANG, Jun ZHOU. A Fast and Efficient FPGA-based Level Set Hardware Accelerator for Image Segmentation[J]. Journal of Electronics & Information Technology, 2021, 43(6): 1525-1532. doi: 10.11999/JEIT210012

基于FPGA的水平集图像分割算法加速器

doi: 10.11999/JEIT210012
基金项目: 国家自然科学基金委员会-中国工程物理研究院NSAF联合基金(U2030204)
详细信息
    作者简介:

    刘野:男,1991年生,博士生,研究方向为图像处理算法与芯片协同设计

    肖剑彪:男,1998年生,硕士生,研究方向为智能感知专用处理芯片设计

    吴飞:男,1997年生,硕士生,研究方向为神经网络硬件加速器设计

    常亮:男,1989年生,副研究员,研究方向为存算一体化人工智能芯片设计

    周军:男,1982年生,教授,研究方向为智能感知算法与芯片协同设计

    通讯作者:

    周军 zhouj@uestc.edu.cn

  • 中图分类号: TN47

A Fast and Efficient FPGA-based Level Set Hardware Accelerator for Image Segmentation

Funds: NSAF (U2030204)
  • 摘要: 水平集算法因其出色的性能,在图像分割领域中得到了广泛的应用。同时,与基于深度学习的图像分割算法相比,水平集算法不需要训练数据,大幅降低了数据标记带来的工作量。然而,目前水平集算法主要是基于软件开发,涉及大量复杂的计算,以及计算的多次迭代,导致较高的处理延时与功耗。为了加快水平集算法的处理速度和降低功耗,该文提出了一种基于FPGA的水平集图像分割算法加速器,其中包含4个设计创新点:任务级并行处理、图像分块像素级并行处理、全流水线处理架构、分时复用的梯度和散度算子处理。实验结果表明,与在CPU上执行的水平集算法相比,该文提出的硬件加速器处理速度提升10.7倍,功耗仅为2.2 W。
  • 图  1  水平集算法处理流程

    图  2  基于FPGA的水平集图像分割算法硬件架构

    图  3  任务级并行处理架构

    图  4  图像分块处理架构

    图  5  本文所提全流水线处理架构

    图  6  分时复用控制器以及时序图

    图  7  实验平台建立和实时演示平台

    图  8  软件和FPGA实现的分割结果对比

    图  9  分割时间对比

    图  10  硬件加速器分割结果轮廓及参考轮廓

    图  11  水平集硬件加速器功耗占比

    表  1  资源利用率

    FPGA型号 时钟频率 (MHz) Regs LUT DSP
    Virtex7 100 40655(6.69%) 30680(10.10%) 307(10.96%)
    下载: 导出CSV
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出版历程
  • 收稿日期:  2021-01-05
  • 修回日期:  2021-04-16
  • 网络出版日期:  2021-04-29
  • 刊出日期:  2021-06-18

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