An Improved Stereo Matching Algorithm for Vehicle Speed Measurement System Based on Spatial and Temporal Image Fusion.

Lei Yang, Qingyuan Li, Xiaowei Song, Wenjing Cai, Chunping Hou, Zixiang Xiong

Abstract read

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Article in Entropy (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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6 authors.

Lei YangSchool of Electronic and Information, Zhongyuan University of Technology, Zhengzhou 450007, China.ORCID 0000-0002-4864-2702

Qingyuan LiSchool of Electronic and Information, Zhongyuan University of Technology, Zhengzhou 450007, China.ORCID 0000-0003-0419-5768

Xiaowei SongSchool of Electronic and Information, Zhongyuan University of Technology, Zhengzhou 450007, China.ORCID 0000-0001-9215-0572

Wenjing CaiSchool of Electronic and Information, Zhongyuan University of Technology, Zhengzhou 450007, China.ORCID 0000-0001-9503-8519

Chunping HouSchool of Electrical and Information Engineering, Tianjin University, Tianjin 300072, China.

Zixiang XiongDepartment of Electrical and Computer Engineering, Texas A&M University, College Station, TX 77843, USA.ORCID 0000-0002-4714-3311

Funding

Education Department of Henan Province 19A510005, 21A510016, 21A520052Human Resources and Social Security Department of Henan Province HRSS2021[36]Science and Technology Department of Henan Province 214200510013Zhongyuan University of Technology Zhongyuan University of Technology

6 · The paper itself

Abstract

This paper proposes an improved stereo matching algorithm for vehicle speed measurement system based on spatial and temporal image fusion (STIF). Firstly, the matching point pairs in the license plate area with obviously abnormal distance to the camera are roughly removed according to the characteristic of license plate specification. Secondly, more mismatching point pairs are finely removed according to local neighborhood consistency constraint (LNCC). Thirdly, the optimum speed measurement point pairs are selected for successive stereo frame pairs by STIF of binocular stereo video, so that the 3D points corresponding to the matching point pairs for speed measurement in the successive stereo frame pairs are in the same position on the real vehicle, which can significantly improve the vehicle speed measurement accuracy. LNCC and STIF can be used not only for license plate, but also for vehicle logo, light, mirror etc. Experimental results demonstrate that the vehicle speed measurement system with the proposed LNCC+STIF stereo matching algorithm can significantly outperform the state-of-the-art system in accuracy.

Indexed as

image fusionLNCCstereo matchingSTIFvehicle speed measurement

Identifiers

PMID34356407

DOI10.3390/e23070866

PMCPMC8305597

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.