基于Zynq的图像角点及边缘检测系统的设计与实现

Design and Implementation of Image Corner and Edge Detection System Based on Zynq

以Zynq芯片为基础,采用软硬件协同设计的方法设计并实现整个系统。Zynq芯片内部采用ARM+FPGA的异构架构,既具备ARM处理器的灵活性,又拥有FPGA并行处理的能力。本系统的设计充分发挥了Zynq芯片的优势,在软硬件划分上,通过ARM处理器来实现图像的采集;图像角点及边缘检测用FPGA来完成,即通过硬件加速提升系统的整体性能。ARM处理器与FPGA通过AXI4总线进行数据交互,在Zynq上实现集图像采集、图像特征提取、图像显示为一体的片上系统。最终系统测试结果表明,采用硬件加速实现图像特征提取的相关算法比在ARM处理器软件上实现的算法的速度提高了6~8倍。

Based on Zynq chip, the whole system is implemented wi th hardware and software co-design method. ARM＋ FPGA is used as internal architecture of the Zynq, so it has both of their advantages, which are flexibility of ARM and parallel processing capabi lity of FPGA. The two advantages are fully used in this system. Image acquisition is implemen-ted by ARM software design. Corner and edge detection is implemented by FPGA hardware design. The ARM processor and FPGA did the data interaction through bus AX14. This system has 3 main funct ions, which are image acquisition, image feature extraction and image display. The results show that this system implemented by Zynq, which used hard-ware acceleration algorithm, is 6 to 8 times faster than that of implemented only by ARM processor.