Image perception hash and structural similarity fusion model for parking lot status recognition

In order to improve the recognition accuracy of parking space change, a new fusion model is proposed. The image-aware hash technique and image structure similarity algorithm are combined to construct a new parking space state combination discriminating index due to the accuracy of the recognition. T...

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Autores principales:	Zhi-Fa Yang, Huan-Jing Zeng, Shi-Wu Li, Yu-Nong Wei, Xian-Jun Fan
Formato:	article
Lenguaje:	EN
Publicado:	Taylor & Francis Group 2019
Materias:	parking detection image perceptual hashing structural similarity fusion model discriminant index Engineering (General). Civil engineering (General) TA1-2040
Acceso en línea:	https://doaj.org/article/ad5ccf0b0b4b437385e8857baa7847db
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id	oai:doaj.org-article:ad5ccf0b0b4b437385e8857baa7847db
record_format	dspace
spelling	oai:doaj.org-article:ad5ccf0b0b4b437385e8857baa7847db2021-11-04T15:51:56ZImage perception hash and structural similarity fusion model for parking lot status recognition2331-191610.1080/23311916.2019.1669390https://doaj.org/article/ad5ccf0b0b4b437385e8857baa7847db2019-01-01T00:00:00Zhttp://dx.doi.org/10.1080/23311916.2019.1669390https://doaj.org/toc/2331-1916In order to improve the recognition accuracy of parking space change, a new fusion model is proposed. The image-aware hash technique and image structure similarity algorithm are combined to construct a new parking space state combination discriminating index due to the accuracy of the recognition. Time is used to define the discriminating threshold of the parking space occupancy condition, so as to construct a vehicle position state discriminating fusion model. Based on the model, the parking lot recognition software was developed, and the parking space recognition of three environmental states, such as uniform illumination, uneven illumination and snowfall, was carried out and the validity of the model was verified.Zhi-Fa YangHuan-Jing ZengShi-Wu LiYu-Nong WeiXian-Jun FanTaylor & Francis Grouparticleparking detectionimage perceptual hashingstructural similarityfusion modeldiscriminant indexEngineering (General). Civil engineering (General)TA1-2040ENCogent Engineering, Vol 6, Iss 1 (2019)
institution	DOAJ
collection	DOAJ
language	EN
topic	parking detection image perceptual hashing structural similarity fusion model discriminant index Engineering (General). Civil engineering (General) TA1-2040
spellingShingle	parking detection image perceptual hashing structural similarity fusion model discriminant index Engineering (General). Civil engineering (General) TA1-2040 Zhi-Fa Yang Huan-Jing Zeng Shi-Wu Li Yu-Nong Wei Xian-Jun Fan Image perception hash and structural similarity fusion model for parking lot status recognition
description	In order to improve the recognition accuracy of parking space change, a new fusion model is proposed. The image-aware hash technique and image structure similarity algorithm are combined to construct a new parking space state combination discriminating index due to the accuracy of the recognition. Time is used to define the discriminating threshold of the parking space occupancy condition, so as to construct a vehicle position state discriminating fusion model. Based on the model, the parking lot recognition software was developed, and the parking space recognition of three environmental states, such as uniform illumination, uneven illumination and snowfall, was carried out and the validity of the model was verified.
format	article
author	Zhi-Fa Yang Huan-Jing Zeng Shi-Wu Li Yu-Nong Wei Xian-Jun Fan
author_facet	Zhi-Fa Yang Huan-Jing Zeng Shi-Wu Li Yu-Nong Wei Xian-Jun Fan
author_sort	Zhi-Fa Yang
title	Image perception hash and structural similarity fusion model for parking lot status recognition
title_short	Image perception hash and structural similarity fusion model for parking lot status recognition
title_full	Image perception hash and structural similarity fusion model for parking lot status recognition
title_fullStr	Image perception hash and structural similarity fusion model for parking lot status recognition
title_full_unstemmed	Image perception hash and structural similarity fusion model for parking lot status recognition
title_sort	image perception hash and structural similarity fusion model for parking lot status recognition
publisher	Taylor & Francis Group
publishDate	2019
url	https://doaj.org/article/ad5ccf0b0b4b437385e8857baa7847db
work_keys_str_mv	AT zhifayang imageperceptionhashandstructuralsimilarityfusionmodelforparkinglotstatusrecognition AT huanjingzeng imageperceptionhashandstructuralsimilarityfusionmodelforparkinglotstatusrecognition AT shiwuli imageperceptionhashandstructuralsimilarityfusionmodelforparkinglotstatusrecognition AT yunongwei imageperceptionhashandstructuralsimilarityfusionmodelforparkinglotstatusrecognition AT xianjunfan imageperceptionhashandstructuralsimilarityfusionmodelforparkinglotstatusrecognition
_version_	1718444670658281472

Image perception hash and structural similarity fusion model for parking lot status recognition

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