Embedded design in neural network and optical flow based high-speed target recognition & tracing

    Research output: Contribution to journalArticlepeer-review

    2 Citations (Scopus)


    © 2015, Xi'an Highway University. All right reserved. High-speed video image processing and high-speed target tracing algorithm for embedded hardware platform were analyzed. Optical flow field algorithm based on neural network was effective to reduce program memory and computing resource requirements of hardware system, which can be more suitable for embedded hardware platforms with DSP (digital signal processing) chip as kernel than traditional strategies. Hopfield Neural Network controller was applied to design a self-corrected filter and taking image signal-to-noise ratio as control index, image preprocessing was carried out for target recognition video image. Compensatory fuzzy neural network controller was applied to optimize optical flow field calculation, which was through using parameter of control smoothness to realize the reduction of average velocity angle error & standard angular error by CFNN (compensatory fuzzy neural network) controller algorithm. The results show that the algorithm can significantly improve the moving target recognition and tracing ability, which proves that it is a more practical and more effective method.
    Original languageEnglish
    Pages (from-to)112-123
    JournalZhongguo Gonglu Xuebao/China Journal of Highway and Transport
    Issue number11
    Publication statusPublished - 2015


    Dive into the research topics of 'Embedded design in neural network and optical flow based high-speed target recognition & tracing'. Together they form a unique fingerprint.

    Cite this