Radial Hahn Moment Invariants for 2D and 3D Image Recognition

doi:10.1007/s11633-017-1071-1

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	Radial Hahn Moment Invariants for 2D and 3D Image Recognition
	Mostafa El Mallahi; Amal Zouhri; Anass El Affar; Ahmed Tahiri; Hassan Qjidaa
发表期刊	International Journal of Automation and Computing
ISSN	1476-8186
	2018
卷号	15 期号:3 页码:277-289
摘要	Recently, orthogonal moments have become efficient tools for two-dimensional and three-dimensional (2D and 3D) image not only in pattern recognition, image vision, but also in image processing and applications engineering. Yet, there is still a major difficulty in 3D rotation invariants. In this paper, we propose new sets of invariants for 2D and 3D rotation, scaling and translation based on orthogonal radial Hahn moments. We also present theoretical mathematics to derive them. Thus, this paper introduces in the first case new 2D radial Hahn moments based on polar representation of an object by one-dimensional orthogonal discrete Hahn polynomials, and a circular function. In the second case, we present new 3D radial Hahn moments using a spherical representation of volumetric image by one-dimensional orthogonal discrete Hahn polynomials and a spherical function. Further 2D and 3D invariants are derived from the proposed 2D and 3D radial Hahn moments respectively, which appear as the third case. In order to test the proposed approach, we have resolved three issues: the image reconstruction, the invariance of rotation, scaling and translation, and the pattern recognition. The result of experiments show that the Hahn moments have done better than the Krawtchouk moments, with and without noise. Simultaneously, the mentioned reconstruction converges quickly to the original image using 2D and 3D radial Hahn moments, and the test images are clearly recognized from a set of images that are available in COIL-20 database for 2D image, and Princeton shape benchmark (PSB) database for 3D image.
关键词	Orthogonal moments two-dimensional and three-dimensional (2D and 3D) radial Hahn moments Hahn polynomials image reconstruction 2D and 3D rotation invariants.
DOI	10.1007/s11633-017-1071-1
引用统计	被引频次：14[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://ir.ia.ac.cn/handle/173211/42409
专题	学术期刊_Machine Intelligence Research
作者单位	Sidi Mohamed Ben Abdellah University, Faculty of Sciences Dhar el Mahraz, CED-ST Center of Doctoral Studies in Sciences and Technologies, Fez, Morocco
推荐引用方式 GB/T 7714	Mostafa El Mallahi,Amal Zouhri,Anass El Affar,et al. Radial Hahn Moment Invariants for 2D and 3D Image Recognition[J]. International Journal of Automation and Computing,2018,15(3):277-289.
APA	Mostafa El Mallahi,Amal Zouhri,Anass El Affar,Ahmed Tahiri,&Hassan Qjidaa.(2018).Radial Hahn Moment Invariants for 2D and 3D Image Recognition.International Journal of Automation and Computing,15(3),277-289.
MLA	Mostafa El Mallahi,et al."Radial Hahn Moment Invariants for 2D and 3D Image Recognition".International Journal of Automation and Computing 15.3(2018):277-289.

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