基于FPGA的运动目标检测与跟踪系统

刘影, 张美娜, 刘洪帅, 杜军

集成电路与嵌入式系统 ›› 2024, Vol. 24 ›› Issue (3) : 62-66.

PDF(1187 KB)
PDF(1187 KB)
集成电路与嵌入式系统 ›› 2024, Vol. 24 ›› Issue (3) : 62-66. DOI: 10.20193/j.ices2097-4191.2024.03.012
研究论文

基于FPGA的运动目标检测与跟踪系统

作者信息 +

Moving object detection and tracking system based on FPGA

Author information +
文章历史 +

摘要

针对传统运动目标检测与跟踪算法计算量大、检测速度慢、鲁棒性差的问题,提出了一种通过动态调整检测区域以实现高效运动目标检测与跟踪的方法。利用改进的帧间差分算法提取运动目标,将目标大小和位置信息分别传给区域裁剪算法和卡尔曼滤波跟踪算法,实现检测范围的缩小和目标跟踪。采用改进后的方法对分辨率为640×480的图像进行实验,检测到目标的大小为66×84,调整后的检测区域大小为132×168,帧间差分检测部分计算量减小了约92.78%,并且根据目标位置进行跟踪的效果较好,在FPGA中验证了此方法的正确性。

Abstract

Aiming at the challenges of intricate computational requirements and a sluggish detection pace,and poor robustness of traditional algorithms for detecting and tracking moving objects,a proposed approach aims to attain efficient moving object detection and tracking by dynamically adjusting the detection area.Utilizing an enhanced inter-frame difference algorithm for the extraction of moving targets,the information regarding the size and location of the target are transmitted to the region cropping algorithm and the Kalman filter tracking algorithm,respectively,to achieve reduced detection range and target tracking.Using an improved method for a resolution of 640× 480 images are used for experiments,and a target size of 66 is detected to 64×84,the adjusted detection area size is 132 ×168,the computation of the inter frame differential detection part is reduced by 92.78%,and the tracking effect based on the target position is better,this approach has been confirmed to be correct in FPGA.

关键词

FPGA / 帧间差分 / 区域裁剪 / 卡尔曼滤波 / 目标跟踪

Key words

FPGA / inter frame difference / regional cropping / kalman filtering / target tracking

引用本文

导出引用
刘影, 张美娜, 刘洪帅, . 基于FPGA的运动目标检测与跟踪系统[J]. 集成电路与嵌入式系统. 2024, 24(3): 62-66 https://doi.org/10.20193/j.ices2097-4191.2024.03.012
LIU Ying, ZHANG Meina, LIU Hongshuai, et al. Moving object detection and tracking system based on FPGA[J]. Integrated Circuits and Embedded Systems. 2024, 24(3): 62-66 https://doi.org/10.20193/j.ices2097-4191.2024.03.012
中图分类号: TP391   

参考文献

[1]
Q YI. FPGA Implementation of Video Capture and Moving Target Detection System[C]// 2018 10th International Conference on Communications, Circuits and Systems (ICCCAS),Chengdu,China, 2018:373-377.doi:10.1109/ICCCAS.2018.8769240.
[2]
V R PAGIRE, C V KULKARNI. FPGA based moving object detection[C]// 2014 International Conference on Computer Communication and Informatics,Coimbatore,India, 2014:1-4.doi: 10.1109/ICCCI.2014.6921802.
[3]
刘海波, 郭乃宏, 周锋, 等. 基于FPGA的改进四帧差分的运动目标检测算法[J]. 电子器件, 2023, 46(4):1089-1095.
LIU H B, GUO N H, ZHOU F, et al. An improved four frame differential motion object detection algorithm based on FPGA[J]. Electronic Devices, 2023, 46(4):1089-1095 (in Chinese).
[4]
朱胜利. Mean Shift及相关算法在视频跟踪中的研究[D]. 杭州: 浙江大学, 2006.
ZHU SH L. Research on Mean Shift and Related Algorithms in Video Tracking[D]. Hangzhou: Zhejiang University, 2006 (in Chinese).
[5]
薛丽霞, 罗艳丽, 王佐成. 基于帧间差分的自适应运动目标检测方法[J]. 计算机应用研究, 2011, 28(4):1551-1552,1559.
XUE L X, LUO Y L, WANG Z CH. Adaptive motion object detection method based on inter frame difference[J]. Computer Application Research, 2011, 28(4):1551-1552,1559 (in Chinese).
[6]
孙挺, 齐迎春, 耿国华. 基于帧间差分和背景差分的运动目标检测算法[J]. 吉林大学学报(工学版), 2016, 46(4):1325-1329.
SUN T, QI Y CH, GENG G H. Motion object detection algorithm based on frame difference and background difference[J]. Journal of Jilin University (Engineering Edition), 2016, 46(4):1325-1329 (in Chinese).
[7]
罗国强, 陈家益. 改进双边滤波与平均γ矫正的图像增强[J]. 传感技术学报, 2022, 35(5):644-649.
LUO G Q, CHEN J Y. Improving bilateral filtering and averaging γ Corrected Image Enhancement[J]. Journal of Sensing Technology, 2022, 35(5):644-649 (in Chinese).
[8]
张志强, 王万玉. 一种改进的双边滤波算法[J]. 中国图象图形学报, 2009, 14(3):443-447.
ZHANG ZH Q, WANG W Y. An improved bilateral filtering algorithm[J]. Chinese Journal of Image and Graphics, 2009, 14(3):443-447 (in Chinese).
[9]
李鹏. 基于FPGA的运动目标检测算法实现[D]. 西安: 西安电子科技大学, 2020.
LI P. Implementation of Motion Object Detection Algorithm Based on FPGA[D]. Xi'an: Xidian University, 2020 (in Chinese).

编辑: 薛士然
PDF(1187 KB)

Accesses

Citation

Detail

段落导航
相关文章

/