Geometric moment invariants to spatial transform and N-fold symmetric blur

doi:10.1016/j.patcog.2021.107887

	Geometric moment invariants to spatial transform and N-fold symmetric blur
	Mo, Hanlin 1,2; Hao, Hongxiang 1,2; Li, Hua 1,2
	2021-07-01
发表期刊	PATTERN RECOGNITION
ISSN	0031-3203
卷号	115 页码:14
摘要	In this paper, we focus on the derivation of blur moment invariants. Blur moment invariants are im-age moment-based features, which preserve their values when the image is convolved by a point-spread function (PSF). Suppose a PSF has N-fold rotational symmetry, we prove its geometric moments of the same order are linearly dependent. Depending on this property, a new approach is proposed to deter-mine whether an existing similarity or affine moment invariant also has invariance to N-fold symmetric blur. Unlike earlier work, this method is not based on complicated operators and construction formu-las. We use it to analyse classical moment-based features, and surprisingly find that five of Hu moment invariants are naturally invariant to N-fold symmetric blur. Meanwhile, we first prove the existence of moment invariants to both affine transform and N-fold symmetric blur. The experiments using synthetic and real blur image datasets are carried out to test these expectations. And the results show that five Hu moment invariants outperform some widely used blur moment invariants and non-moment image features in image retrieval, classification and template matching. (c) 2021 Elsevier Ltd. All rights reserved.
关键词	Blurred image Blur invariants Moment invariants Spatial transform N-fold symmetry Object recognition Template matching
DOI	10.1016/j.patcog.2021.107887
收录类别	SCI
语种	英语
资助项目	National Key R&D Program of China[2017YFB1002703] ; National Key Basic Research Planning Project of China[2015CB554507] ; National Natural Science Foundation of China[61227802] ; National Natural Science Foundation of China[61379082]
WOS研究方向	Computer Science ; Engineering
WOS类目	Computer Science, Artificial Intelligence ; Engineering, Electrical & Electronic
WOS记录号	WOS:000639745600008
出版者	ELSEVIER SCI LTD
引用统计	被引频次：2[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://119.78.100.204/handle/2XEOYT63/16655
专题	中国科学院计算技术研究所期刊论文_英文
通讯作者	Mo, Hanlin
作者单位	1.Chinese Acad Sci, Inst Comp Technol, Key Lab Intelligent Informat Proc, Beijing, Peoples R China 2.Univ Chinese Acad Sci, Beijing, Peoples R China
推荐引用方式 GB/T 7714	Mo, Hanlin,Hao, Hongxiang,Li, Hua. Geometric moment invariants to spatial transform and N-fold symmetric blur[J]. PATTERN RECOGNITION,2021,115:14.
APA	Mo, Hanlin,Hao, Hongxiang,&Li, Hua.(2021).Geometric moment invariants to spatial transform and N-fold symmetric blur.PATTERN RECOGNITION,115,14.
MLA	Mo, Hanlin,et al."Geometric moment invariants to spatial transform and N-fold symmetric blur".PATTERN RECOGNITION 115(2021):14.