Rotation and translation invariants of Gaussian-Hermite moments

被引:46
|
作者
Yang, Bo [1 ]
Li, Gengxiang [1 ]
Zhang, Huilong [2 ]
Dai, Mo [1 ]
机构
[1] Univ Bordeaux 3, Inst EGID, F-33607 Pessac, France
[2] Inst Math Bordeaux, UMR 5251, F-33405 Talence, France
关键词
Orthogonal polynomials; Gaussian-Hermite moments; Moment invariants; Rotation and translation invariants; IMAGE-ANALYSIS; PATTERN-RECOGNITION; SCALE INVARIANTS;
D O I
10.1016/j.patrec.2011.03.012
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Geometric moment invariants are widely used in many fields of image analysis and pattern recognition since their first introduction by Hu in 1962. A few years ago, Flusser has proved how to find the independent and complete set of geometric moment invariants corresponding to a given order. On the other hand, the properties of orthogonal moments show that they can be recognized as useful tools for image representation and reconstruction. Therefore, derivation of invariants from orthogonal moments becomes an interesting subject and some results have been reported in literature. In this paper, we propose to use a family of orthogonal moments, called Gaussian-Hermite moments and defined with Hermite polynomials, for deriving their corresponding invariants. The rotation invariants of Gaussian-Hermite moments can be achieved algebraically according to a property of Hermite polynomials. This approach is definitely different from the conventional methods which derive orthogonal moment invariants either by image normalization or by an expression as a linear combination of the invariants of geometric moments. One significant conclusion drawn is that the rotation invariants of Gaussian-Hermite moments have the identical forms to those of geometric moments. This coincidence is also proved mathematically in the appendix of the paper. Moreover, the translation invariants could be easily constructed by translating the coordinate origin to the image centroid. The invariants of Gaussian-Hermite moments both to rotation and to translation are accomplished by the combination of these two kinds of invariants. Their rotational and translational invariance is evaluated by a set of transformed gray-level images. The numeric stabilities of the proposed invariant descriptors are also discussed under both noise-free and noisy conditions. The computational complexity and time for implementing such invariants are analyzed as well. In addition to this, the better performance of the Gaussian-Hermite invariants is experimentally demonstrated by pattern matching in comparison with geometric moment invariants. (C) 2011 Elsevier B.V. All rights reserved.
引用
收藏
页码:1283 / 1298
页数:16
相关论文
共 50 条
  • [21] Application of Improved Gaussian-Hermite Moments in Intelligent Parking System
    He, Xing
    Wang, Lin
    Zuo, Zhongyou
    PROCEEDINGS OF THE 3RD INTERNATIONAL CONFERENCE ON ELECTRICAL AND INFORMATION TECHNOLOGIES FOR RAIL TRANSPORTATION (EITRT) 2017: ELECTRICAL TRACTION, 2018, 482 : 689 - 699
  • [22] A Blind Estimation for Speckle Noise based on Gaussian-Hermite Moments
    Miao, Ma
    Xue, Zheng
    Zhao, Pei
    2016 INTERNATIONAL SYMPOSIUM ON COMPUTER, CONSUMER AND CONTROL (IS3C), 2016, : 829 - 832
  • [23] Moving object detection using orthogonal Gaussian-Hermite moments
    Wu, YF
    Shen, J
    VISUAL COMMUNICATIONS AND IMAGE PROCESSING 2004, PTS 1 AND 2, 2004, 5308 : 841 - 849
  • [24] Fast computation of accurate Gaussian-Hermite moments for image processing applications
    Hosny, Khalid M.
    DIGITAL SIGNAL PROCESSING, 2012, 22 (03) : 476 - 485
  • [25] Localization of singular points in fingerprint images based on the Gaussian-Hermite moments
    Wang, Lin
    Dai, Mo
    Ruan Jian Xue Bao/Journal of Software, 2006, 17 (02): : 242 - 249
  • [26] New features extraction and application based on Gaussian-Hermite moments in fingerprint classification
    Wang, Lin
    Dai, Mo
    2005 IEEE/SP 13th Workshop on Statistical Signal Processing (SSP), Vols 1 and 2, 2005, : 413 - 418
  • [27] Mosaic of Printed Circuit Board Image Based on Gaussian-Hermite Moment Invariants
    ZHANG Yuye
    YANG Bo
    WuhanUniversityJournalofNaturalSciences, 2017, 22 (05) : 380 - 386
  • [28] Bayesian face recognition using 2D Gaussian-Hermite moments
    Rahman, S. M. Mahbubur
    Lata, Shahana Parvin
    Howlader, Tamanna
    EURASIP JOURNAL ON IMAGE AND VIDEO PROCESSING, 2015,
  • [29] An Intelligence Monitoring Technique for Abnormal Water Surface Based on Gaussian-Hermite Moments
    Wu, Youfu
    Li, Fang
    Pan, Chunyan
    Wu, Jing
    2017 IEEE 2ND ADVANCED INFORMATION TECHNOLOGY, ELECTRONIC AND AUTOMATION CONTROL CONFERENCE (IAEAC), 2017, : 41 - 44
  • [30] A new SVM-based image watermarking using Gaussian-Hermite moments
    Wang Xiang-Yang
    Miao E-No
    Yang Hong-Ying
    APPLIED SOFT COMPUTING, 2012, 12 (02) : 887 - 903