穆向阳, 徐益. 一种快速焊缝图像处理的FPGA实现方法[J]. 制造技术与机床, 2023, (7): 163-168. DOI: 10.19287/j.mtmt.1005-2402.2023.07.025
引用本文: 穆向阳, 徐益. 一种快速焊缝图像处理的FPGA实现方法[J]. 制造技术与机床, 2023, (7): 163-168. DOI: 10.19287/j.mtmt.1005-2402.2023.07.025
MU Xiangyang, XU Yi. An FPGA implementation method for fast weld image processing[J]. Manufacturing Technology & Machine Tool, 2023, (7): 163-168. DOI: 10.19287/j.mtmt.1005-2402.2023.07.025
Citation: MU Xiangyang, XU Yi. An FPGA implementation method for fast weld image processing[J]. Manufacturing Technology & Machine Tool, 2023, (7): 163-168. DOI: 10.19287/j.mtmt.1005-2402.2023.07.025

一种快速焊缝图像处理的FPGA实现方法

An FPGA implementation method for fast weld image processing

  • 摘要: 针对串行架构的处理器及通用计算机实现管道焊缝检测实时性不足的情况,提出了一种基于FPGA的快速管道焊缝图像处理算法。在采集管道焊缝图像过程中,会存在噪声干扰图像,直接影响缺陷的边缘检测与目标识别。将FPGA的并行计算及流水线技术运用到中值滤波和Sobel边缘检测算法中,实现模块之间的并行处理,并且在流水线协同下通过卷积核移位执行像素操作,实现了一种快速管道焊缝图像处理算法,发挥了FPGA计算速度上的优势。实验证明:对于一幅600×400的图像,在时钟频率为100 MHz的环境下,从像素读取到图像处理完成只需9.568 21 ms,相较于通用计算机上实现图像处理算法有极大的速度提升,该算法能够有效提升图像处理的执行效率,可用于高实时性的管道焊缝图像处理。

     

    Abstract: A fast pipeline weld image processing algorithm based on FPGA is proposed for the lack of real-time detection of pipeline weld by serial architecture processor and general computer. In the process of collecting pipeline weld image, there will be noise interference image, which directly affects the edge detection and target recognition of defects. The parallel computing and pipeline technology of FPGA are applied to median filtering and Sobel edge detection algorithm to realize parallel processing between modules, and pixel operation is performed by convolution kernel shift under pipeline coordination. A fast pipeline weld image processing algorithm is realized, which gives full play to the advantages of FPGA computing speed. Experiments show that for a 600 × 400 image, in the environment of a clock frequency of 100 MHz, it only takes 9.56821 ms from pixel reading to image processing completion. Compared with the general computer, the image processing algorithm has a great speed improvement. The algorithm can effectively improve the execution efficiency of image processing and can be used for high real-time pipeline weld image processing.

     

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