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一种基于局部特征分块的目标跟踪算法

A target tracking algorithm based on local feature segmentation

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摘要

为了解决传统目标跟踪算法在天空背景下面临高能激光反射时图像像素?#21494;?#20998;布发生剧烈变化, 从而导致目标遮挡或丢失的问题, 采用一种基于局部特征分块思想的相关跟踪算法, 根据局部特征对跟踪模板进行了分块处理, 计算并选取其中特征稳定度高的块模板, 在跟踪区域内对每个块做模板匹配, 并进行了理论分析和试验验证。结果表明, ?#30431;?#27861;在强光干扰下能够有效地对目标实时稳定跟踪, 且图像处理延迟时间在2ms?#38405;凇?#35813;研究对基于高能激光发射下的超高精度跟踪系统工作性能的保证是有帮助的。

Abstract

In order to solve the problem of occlusion or loss of targets caused by drastic change in gray distribution of image pixels by using traditional target tracking algorithms under high-energy laser reflection in the sky background, a correlation tracking algorithm based on local feature segmentation was adopted. The tracking template was divided into blocks according to local features. The block templates with high feature stability were calculated and selected. Template matching was performed for each block in the tracking area. The theoretical analysis and experimental verification were carried out. The results show that the algorithm can track the target stably in real time under strong light interference. And the image processing delay time is less than 2ms. This research is helpful to ensure the performance of ultra-high precision tracking system based on high-energy laser emission.

Newport宣传-MKS新实验室计划
补充资料

中图分类号:TP391

DOI:10.7510/jgjs.issn.1001-3806.2019.04.023

所属栏目:光通信与光信息技术

收稿日期:2018-08-06

修改稿日期:2018-12-21

网络出版日期:--

作者单位    点击查看

王宇慧:中国船舶重工集团公司 第七一三研究所, 郑州 450000
徐志远:中国船舶重工集团公司 第七一三研究所, 郑州 450000
叶德茂:中国船舶重工集团公司 第七一三研究所, 郑州 450000

联系人作者:王宇慧([email protected])

备注:王宇慧(1989-), 女, 硕士, 工程师, ?#31181;?#35201;从事目标识别跟踪图像处理等方面的研究。

【1】YIN H P, CHEN B, CHAI Y, et al. Vision-based object detection and tracking: A review[J]. Acta Automatica Sinica, 2016, 42(10): 1466-1489(in Chinese).

【2】QIU X R, PENG L, LIU Q Sh. Object tracking algorithm based on superpixel and discriminative sparsity[J]. Computer Engineering and Applications, 2018, 54(15): 1-5(in Chinese).

【3】LU H Ch, LI P X, WANG D. Visual object tracking: A survey[J]. Pattern Recognition and Artificial Intelligence, 2018, 31(1): 61-76(in Chinese).

【4】BAKER E S, DEGROAT R D. A correlation-based subspace tracking algorithm[J]. IEEE Transactions on Signal Processing, 1998, 46(11): 3112-3116.

【5】CAO H Y. Research and application of target tracking algorithm based on DSP platform [D]. Xi’an: Xidian University, 2017: 1-3(in Chin-ese).

【6】ZITOV B, FLUSSER J. Image registration methods: a survey[J]. Image & Vision Computing, 2003, 21(11): 977-1000.

【7】CHEN H Y, YANG Y. Rapid registration algorithm of large-scale images based on normalized gradient phase correlation [J]. Pattern Re-cognition and Artificial Intelligence, 2015, 28(8): 694-701(in Ch-inese).

【8】CHIN F J, FANG Q, ZHANG T, et al. A fast critical arrhythmic ECG waveform identification method using cross-correlation and multiple template matching[C]//The 32nd Annual International Conference of IEEE.New York,USA: IEEE,2010: 1922-1925. XING C J, WEN L L, HE S Q. Target tracking of NCC fast matching method based on sequential similarity detection[J]. Electronic Design Engineering,2015, 23(2): 187-190(in Chinese).

【9】ZHANG G S, CHEN D Sh, QIU H T, et al. Design of high speed image tracking system based on FPGA[J]. Microelectronics & Computer, 2017, 34(4): 13-16(in Chinese).

【10】DONG Y M. Visual object tracking based on correlation filters [D]. Beijing: Beijing Institute of Technology, 2015: 5-13(in Chinese).

【11】XU Y Q, SHI Q H, QU Y D, et al. Study of image registration algorithm based on genetic algorithm [J]. Computer Science, 2016, 43(11A): 229-232(in Chinese).

【12】SONG J H,YAN B L. Research on rapid mosaic technology of UAV aerial image based on SIFT [J].Computer Applications and Software, 2018, 35(2): 230-234(in Chinese).

【13】ZHENG T, HAO X M, CHEN M. Mean Shift motion detection and tracking based on feature matching estimation[J]. Transducer and Microsystem Technologies, 2018, 37(7): 135-138(in Chinese).

【14】ZHU H N, XU M M, SHEN Y. Research on multi video vehicle tracking based on mean shift [J]. Computer Science, 2018, 45(6A): 220-226(in Chinese).

【15】YANG K, LIU G H, XU F. Mean shift tracking algorithm based on BCH and HOG[J]. Transducer and Microsystem Technologies, 2018, 37(7): 138-141(in Chinese).

【16】SIDRAM M H, BHAJANTRI N U. Enhancement of mean shift tracking through joint histogram of color and color coherence vector[M]. New Deli,India: Springer, 2014: 547-555.

【17】WEI B G, ZHAO S T, WEN X L. Multi-region tracking based on local histogram[J]. Computer Engineering and Application, 2018, 54(14): 26-33(in Chinese).

【18】HOU T J. Design and implementation of image enhancement and template matching system based on FPGA [D]. Beijing: University of Chinese Academy of Sciences, 2016: 3-16(in Chinese).

【19】FENG W, WANG Y D, ZHANG L. Deep feature extraction and classification recognition algorithm based on weighting and dimension reduction[J]. Laser Technology, 2018, 42(5): 666-672(in Chin-ese).

【20】CHEN J L, MIAO D, KANG B, et al. Research of target tracking based on Kalman filtering and template matching[J]. Optics & Optoelectronic Technology, 2014, 12(6): 9-12(in Chinese).

引用该论文

WANG Yuhui,XU Zhiyuan,YE Demao. A target tracking algorithm based on local feature segmentation[J]. Laser Technology, 2019, 43(4): 569-573

王宇慧,徐志远,叶德茂. 一种基于局部特征分块的目标跟踪算法[J]. 激光技术, 2019, 43(4): 569-573

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