Image Shadow Detection and Removal Based on Region Matching of Intelligent Computing.
Journal
Computational intelligence and neuroscience
ISSN: 1687-5273
Titre abrégé: Comput Intell Neurosci
Pays: United States
ID NLM: 101279357
Informations de publication
Date de publication:
2022
2022
Historique:
received:
08
03
2022
revised:
17
03
2022
accepted:
02
04
2022
entrez:
2
5
2022
pubmed:
3
5
2022
medline:
4
5
2022
Statut:
epublish
Résumé
Shadow detection and removal play an important role in the field of computer vision and pattern recognition. Shadow will cause some loss and interference to the information of moving objects, resulting in the performance degradation of subsequent computer vision tasks such as moving object detection or image segmentation. In this paper, each image is regarded as a small sample, and then a method based on material matching of intelligent computing between image regions is proposed to detect and remove image shadows. In shadow detection, the proposed method can be directly used for detection without training and ensures the consistency of similar regions to a certain extent. In shadow removal, the proposed method can minimize the influence of shadow removal operation on other features in the shadow region. The experiments on the benchmark dataset demonstrate that the proposed approach achieves a promising performance, and its improvement is more than 6% in comparison with several advanced shadow detection methods.
Identifiants
pubmed: 35498207
doi: 10.1155/2022/7261551
pmc: PMC9045973
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
7261551Informations de copyright
Copyright © 2022 Junying Feng et al.
Déclaration de conflit d'intérêts
The authors declare that there are no conflicts of interest regarding the publication of this paper.
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