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A Moving Shadow Elimination Method Based on Fusion of Multi-Feature

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成果类型:
期刊论文
作者:
Zhang, Hongrui;Qu, Shaocheng*;Li, Huan;Luo, Jing;Xu, Wenjun
通讯作者:
Qu, Shaocheng
作者机构:
[Zhang, Hongrui; Qu, Shaocheng; Luo, Jing; Xu, Wenjun] Cent China Normal Univ, Coll Phys Sci & Technol, Wuhan 430079, Peoples R China.
[Li, Huan] Army Special Operat Coll, Dept Special Technol, Guilin 541000, Peoples R China.
通讯机构:
[Qu, Shaocheng] C
Cent China Normal Univ, Coll Phys Sci & Technol, Wuhan 430079, Peoples R China.
语种:
英文
关键词:
HSV;region growth;Shadow elimination;UESILTP
期刊:
IEEE ACCESS
ISSN:
2169-3536
年:
2020
卷:
8
页码:
63971-63982
基金类别:
This work was supported in part by the National Natural Science Foundation of China under Grant 61673190/F030101, and in part by the Self-Determined Research Funds of Central China Normal University (CCNU) from the Colleges’ Basic Research and Operation of the Ministry of Education (MOE) under Grant CCNU18TS042.
机构署名:
本校为第一且通讯机构
院系归属:
物理科学与技术学院
摘要:
Moving shadow elimination plays an important role in the field of moving object detection. However, the accuracy of shadow elimination is an open question, due to illumination and complex texture. Furthermore, the problem of misclassification of moving object caused by shadow has also become increasingly serious. To address this problem, this paper presents a moving shadow elimination algorithm based on the fusion of multi-feature pattern, which can enhance the accuracy of moving object detection system. In this approach, a dual-channel HSV color space feature and a uniform extended scale inva...

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